Publications

Conference Papers

  1. 2026
  2. Do Natural Language Interpretability Methods Convey Privileged Information? Millicent Li, Alberto Mario Ceballos Arroyo, Giordano Rogers, Naomi Saphra, Byron C Wallace Proceedings of the International Conference on Machine Learning (ICML), 2026.
  3. Interpretability Can Be Actionable Hadas Orgad, Fazl Barez, Tal Haklay, Isabelle Lee, Marius Mosbach, Anja Reusch, Naomi Saphra, Byron C Wallace, Sarah Wiegrefe, Eric Wong, Ian Tenney, Mor Geva Proceedings of the International Conference on Machine Learning (ICML), 2026.
  4. Faithfulness vs. Safety: Evaluating LLM Behavior Under Counterfactual Medical Evidence Kaijie Mo, Siddhartha Venkatayogi, Chantal Shaib, Ramez Kouzy, Wei Xu, Byron C Wallace, Junyi Jessy Li Proceedings of the Findings of Conference of the Association for Computational Linguistics (ACL), 2026.
  5. Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine Sebastian Joseph, Lily Chen, Barry Wei, Michael Mackert, Iain J Marshall, Paul Pu Liang, Ramez Kouzy, Byron C Wallace, Junyi Jessy Li Proceedings of the Findings of Conference of the Association for Computational Linguistics (ACL), 2026.
  6. Can SAEs reveal and mitigate racial biases of LLMs in healthcare? Hiba Ahsan, Byron C Wallace Proceedings of the International Conference on Learning Representations (ICLR), 2026.
  1. 2025
  2. Standardizing the Measurement of Text Diversity: A Tool and Comparative Analysis Chantal Shaib, Venkata S Govindarajan, Joe Barrow, Jiuding Sun, Alexa Siu, Byron C Wallace, Ani Nenkova Proceedings of the International Joint Conference on Natural Language Processing and Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP/AACL), System Demonstrations, 36--46, 2025.
  3. Do Automatic Factuality Metrics Measure Factuality? A Critical Evaluation Sanjana Ramprasad, Byron C Wallace Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
  4. Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models Chantal Shaib, Vinith Menon Suriyakumar, Byron C Wallace, Marzyeh Ghassemi Proceedings of the Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
  5. Elucidating Mechanisms of Demographic Bias in LLMs for Healthcare Hiba Ahsan, Arnab Sen Sharma, Silvio Amir, David Bau, Byron C Wallace Proceedings of the Findings of Empirical Methods in Natural Language Processing (EMNLP), 2025.
  6. The Dual-Route Model of Induction Sheridan Feucht, Eric Todd, Byron C Wallace, David Bau Proceedings of the Conference on Language Modeling (COLM), 2025.
  7. Who Taught You That? Tracing Teachers in Model Distillation Somin Wadhwa, Chantal Shaib, Silvio Amir, Byron C Wallace Proceedings of the Findings of Conference of the Association for Computational Linguistics (ACL), 2025.
  8. Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature? Hye Sun Yun, Karen Y.C. Zhang, Ramez Kouzy, Iain James Marshall, Junyi Jessy Li, Byron C Wallace Proceedings of the ACM Conference on Health, Inference, and Learning (CHIL), 2025.
  9. NNsight and NDIF: Democratizing Access to Foundation Model Internals Jaden Fried Fiotto-Kaufman, Alexander Russell Loftus, Eric Todd, Jannik Brinkmann, Koyena Pal, Dmitrii Troitskii, Michael Ripa, Adam Belfki, Can Rager, Caden Juang, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Nikhil Prakash, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C. Wallace, David Bau Proceedings of the International Conference on Learning Representations (ICLR), 2025.
  1. 2024
  2. Investigating Mysteries of CoT-Augmented Distillation Somin Wadwha, Silvio Amir, Byron C. Wallace Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 6071--6086, 2024.
  3. Detection and Measurement of Syntactic Templates in Generated Text Chantal Shaib, Yanai Elaza, Jessy Junyi Li, Byron C. Wallace Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 6416--6431, 2024.
  4. Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs Sheridan Feucht, David Atkinson, Byron C. Wallace, David Bau Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 9727--9739, 2024.
  5. Learning from Natural Language Explanations for Generalizable Entity Matching Somin Wadwha, Adit Krishnan, Runhui Wang, Byron C. Wallace, Luyang Kong Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 6114--6129, 2024.
  6. Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models Hye Sun Yun, David Pogrebitskiy, Iain J Marshall, Byron C Wallace Proceedings of Machine Learning for Healthcare (MLHC), 2024.
  7. Infolossqa: Characterizing and recovering information loss in text simplification Jan Trienes, Sebastian Joseph, J{\"o}rg Schl{\"o}tterer, Christin Seifert, Kyle Lo, Wei Xu, Byron C Wallace, Junyi Jessy Li Proceedings of the Conference of the Association for Computational Linguistics (ACL), 4263--4294, 2024.
  8. FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence Sebastian Antony Joseph, Lily Chen, Jan Trienes, Hannah Louisa G{\"o}ke, Monika Coers, Wei Xu, Byron C Wallace, Junyi Jessy Li Proceedings of the Conference of the Association for Computational Linguistics (ACL), 8437--8464, 2024.
  9. Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges Hiba Ahsan, Denis Jered McInerney, Jisoo Kim, Christopher A Potter, Geoffrey Young, Silvio Amir, Byron C Wallace Proceedings of the ACM Conference on Health, Inference, and Learning (CHIL), 2024.
  10. On-the-fly Definition Augmentation of LLMs for Biomedical NER Monica Munnangi, Sergey Feldman, Byron C Wallace, Silvio Amir, Tom Hope, Aakanksha Naik Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 3833--3854, 2024.
  11. Towards Reducing Diagnostic Errors with Interpretable Risk Prediction Denis Jered McInerney, William Dickinson, Lucy C. Flynn, Andrea C Young, Geoffrey Young, Jan-Willem van de Meent, Byron C Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 7193--7210, 2024.
  12. Evaluating the Zero-shot Robustness of Instruction-tuned Language Models Jiuding Sun, Chantal Shaib, Byron C. Wallace Proceedings of the International Conference on Learning Representations (ICLR), 2024. Spotlight (top 5\
  13. LLMs Represent Contextual Tasks as Compact Function Vectors Eric Todd, Millicent Li, Arnab Sen Sharma, Aaron Mueller, Byron C Wallace, David Bau Proceedings of the International Conference on Learning Representations (ICLR), 2024.
  14. Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains {Sanjana Ramprasad, Kundan Krishna, Zachary Chase Lipton, Byron C Wallace} Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), 50--59, 2024.
  15. Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study {Zhaoyue Sun, Gabriele Pergola, Byron C Wallace, Yulan He} Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), 344--357, 2024.
  1. 2023
  2. Multilingual Simplification of Medical Texts Sebastian Joseph, Kathryn Kazanas, Keziah Reina, Vishnesh J. Ramanathan, Wei Xu, Byron C. Wallace, Junyi Jessy Li Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 16662--16692, 2023.
  3. Anticipating Subsequent Tokens from a Single Hidden State Koyena Pal, Kiuding Sun, Andrew Yuan, Byron C. Wallace, David Bau Proceedings of the SIGNLL Conference on Computational Natural Language Learning (CoNLL), 548--560, 2023.
  4. Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews Hye Sun Yun, Iain J. Marshall, Thomas Trikalinos, Byron C. Wallace Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 10122--10139, 2023.
  5. USB: A Unified Summarization Benchmark Across Tasks and Domains Kundan Krishna, Prakhar Gupta, Sanjana Ramprasad, Byron C. Wallace, Jeffrey P. Bigham, Zachary C. Lipton Proceedings of Findings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 8826–-8845, 2023.
  6. CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace Proceeding of Findings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 8477--8494, 2023.
  7. Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs Somin Wadhwa, Jay DeYoung, Benjamin Nye, Silvio Amir, Byron C. Wallace Proceedings of Machine Learning for Healthcare (MLHC), 754--771, 2023.
  8. Accomodating User Expressivity while Maintaining Safety for a Virtual Alcohol Misuse Counselor Stefán Ólafsson, Paola Pedrelli, Byron C. Wallace, Timothy Bickmore Proceedings of the Conference on Intelligent Virtual Agents (IVA), 2023.
  9. Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations Lucy Lu Wang, Yulia Otmakhova, Jay DeYoung, Thinh Hung Truong, Bailey E. Kuehl, Erin Bransom, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), 9871--9889, 2023.
  10. Summarizing, Simplifying, and Synthesizing Medical Evidence using GPT-3 (with Varying Success) Chantal Shaib, Millicent Liaw Li, Sebastian A. Joseph, Iain J. Marshall, Junyi Jessy Li, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), 1387--1407, 2023.
  11. Revisiting Relation Extraction in the era of Large Language Models Somin Wadhwa, Silvio Amir, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), 15566--15589, 2023.
  12. Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challenges Sanjana Ramprasad, Denis Jered McInerney, Iain J. Marshall, Byron C. Wallace Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), System Demonstrations, 236--247, 2023.
  13. How Many and Which Training Points Would Need to be Removed to Flip this Prediction? Jinhan Yang, Sarthak Jain, Byron C. Wallace Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2571--2584, 2023.
  14. RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media Somin Wadhwa, Vivek Khetan, Silvio Amir, Byron C. Wallace Proceedings of the Findings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), 809--827, 2023.
  1. 2022
  2. That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 3626--3648, 2022.
  3. PHEE: A Dataset for Pharmacovigilance Event Extraction from Text Zhaoyue Sun, Jiazheng Li, Gabriele Pergola, Byron C. Wallace, Bino John, Nigel Greene, Joseph Kim, Yulan He Proceedings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 2022.
  4. Influence Functions for Sequence Tagging Models Sarthak Jain, Varun Manjunatha, Byron C. Wallace, Ani Nenkova Proceedings of the Findings of the Conference on Empirical Methods for Natural Language Processing (EMNLP), 824--839, 2022.
  5. Self-Repetition in Abstractive Neural Summarizers Nikita Salkar, Thomas Trikalinos, Byron C. Wallace, Ani Nenkova Proceedings of the Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL), 341--350, 2022.
  6. Combining Feature and Instance Attribution to Detect Artifacts Pouya Pezeshkpour, Sarthak Jain, Sameer Singh, Byron C. Wallace Proceedings of the Findings of the Conference of the Association for Computational Linguistics (ACL), 1934--1946, 2022.
  7. Evaluating Factuality in Text Simplification Ashwin Devaraj, William Berkeley Sheffield, Byron C Wallace, Junyi Jessy Li Proceedings of the Conference of the Association for Computational Linguistics (ACL), 7331--7345, 2022. ACL 2022 Outstanding Paper
  1. 2021
  2. Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data David Lowell, Brian Howard, Zachary C. Lipton, Byron C. Wallace Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021.
  3. Disentangling Representations of Text by Masking Transformers Xiongyi Zhang, Jan-Willem van de Meent, Byron Wallace Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 778--791, 2021.
  4. Biomedical Interpretable Entity Representations Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron Wallace, Kush Varshney Proceedings of the Findings of the Association for Computational Linguistics (ACL), 3547--3561, 2021.
  5. An Empirical Comparison of Instance Attribution Methods for NLP Pouya Pezeshkpour, Sarthak Jain, Byron Wallace, Sameer Singh Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 967--975, 2021.
  6. On the Impact of Random Seeds on the Fairness of Clinical Classifiers Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 3808--3823, 2021.
  7. Paragraph-level Simplification of Medical Texts Ashwin Devaraj, Iain Marshall, Byron C. Wallace, Junyi Jessy Li Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 4972--4984, 2021.
  8. Does BERT Pretrained on Clinical Notes Reveal Sensitive Data? Eric Lehman, Sarthak Jain, Karl Pichotta, Yoav Goldberg, Byron C. Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 946--959, 2021.
  9. Understanding Clinical Trial Reports: Extracting Medical Entities and Their Relations Benjamin E. Nye, Jay DeYoung, Eric Lehman, Ani Nenkova, Iain J. Marshall, Byron C. Wallace Proceedings of AMIA Informatics Summit, 2021. Recipient of the Best Student Paper Award.
  10. Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization Byron C. Wallace, Sayantan Saha, Frank Soboczenski, Iain J. Marshall Proceedings of AMIA Informatics Summit, 2021.
  1. 2020
  2. Query-Focused EHR Summarization to Aid Imaging Diagnosis Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace Proceedings of Machine Learning in Health Care (MLHC), 2020.
  3. Semi-Automating Knowledge Base Construction for Cancer Genetics Somin Wadhwa, Kanhua Yin, Kevin S. Hughes, Byron C. Wallace Proceedings of the Conference on Automated Knowledge Base Construction (AKBC), 2020.
  4. ERASER: A Benchmark to Evaluate Rationalized NLP Models Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, Eric Lehman, Caiming Xiong, Richard Socher, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), 4443--4458, 2020.
  5. Learning to Faithfully Rationalize by Construction Sarthak Jain, Sarah Wiegreffe, Yuval Pinter, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), 4459--4473, 2020.
  6. Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time Benjamin Nye, Ani Nenkova, Iain J. Marshall, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), System Demonstrations, 63--69, 2020.
  7. Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions Xiaochuang Han, Byron C. Wallace, Yulia Tsvetkov Proceedings of the Conference of the Association for Computational Linguistics (ACL), 5553--5563, 2020.
  8. MMiDaS-AE: Multi-modal Missing Data aware Stacked Autoencoder for Biomedical Abstract Screening Eric Lee, Byron C. Wallace, Karla Galaviz, Joyce C. Ho Proceedings of the ACM Conference on Health, Inference, and Learning (CHIL), 139--150, 2020.
  9. Towards a Computational Framework for Automating Substance Use Counseling with Virtual Agents Stefan Olafsson, Byron C. Wallace, Timothy Bickmore Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 966--974, 2020.
  1. 2019
  2. Practical Obstacles to Deploying Active Learning David Lowell, Zachary Lipton, Byron C. Wallace Proceedings of Empirical Methods in Natural Language Processing (EMNLP), 21--30, 2019.
  3. Are Online Reviews of Physicians BiasedAgainst Female Providers? Avijit Thawani, Michael J. Paul, Urmimala Sarkar, Byron C. Wallace Proceedings of Machine Learning in Health Care (MLHC), 406--423, 2019.
  4. Attention is not Explanation Sarthak Jain, Byron C. Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 3543--3556, 2019.
  5. Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction Yinfei Yang, Oshin Agarwal, Chris Tar, Byron C. Wallace, Ani Nenkova Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 1471--1480, 2019.
  6. Inferring Which Medical Treatments Work from Reports of Clinical Trials Eric Lehman, Jay DeYoung, Regina Barzilay, Byron C. Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 3705--3717, 2019.
  7. Structured neural topic models for reviews Babak Esmaeili, Hongyi Huang, Byron Wallace, Jan-Willem van de Meent Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATs), 3429--3439, 2019.
  8. Explainable Modeling of Annotations in Crowdsourcing An Thanh Nguyen, Matthew Lease, Byron C. Wallace Proceedings of the Annual ACM Intelligent User Interfaces (IUI) conference, 575--579, 2019.
  9. Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data Ramin Mohammadi, Sarthak Jain, Stephen Agboola, Ramya Palacholla, Sagar Kamarthi, Byron C. Wallace Proceedings of the AMIA Informatics Summit, 2019.
  1. 2018
  2. Learning Disentangled Representations of Texts with Application to Biomedical Abstracts Sarthak Jain, Edward Banner, Jan-Willem van de Meent, Iain J. Marshall, Byron C. Wallace Proceedings of Empirical Methods in Natural Language Processing (EMNLP), 4683–4693, 2018.
  3. Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding Gaurav Singh, James Thomas, Iain J. Marshall, John Shawe-Taylor, Byron C. Wallace Proceedings of Empirical Methods in Natural Language Processing (EMNLP), 2837--2842, 2018.
  4. Believe it or not: Designing a Human-AI Partnership for Mixed-Initiative Fact-Checking An Thanh Nguyen, Byron C.\ Wallace, Matthew Lease Proceedings of the ACM User Interface Software and Technology Symposium (UIST), 189--199, 2018.
  5. A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature Benjamin Nye, Jessy Li, Roma Patel, Yinfei Yang, Iain Marshall, Ani Nenkova, Byron C. Wallace Proceedings of the Conference of the Association for Computational Linguistics (ACL), 197--207, 2018.
  6. Syntactic Patterns Improve Information Extraction for Medical Search Roma Patel, Yinfei Yang, Iain Marshall, Ani Nenkova, Byron C. Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 371--377, 2018.
  7. An Interpretable Joint Graphical Model for Fact-Checking from Crowds An Thanh Nguyen, Aditya Kharosekar, Matthew Lease, Byron C.\ Wallace Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 1511--1518, 2018.
  1. 2017
  2. A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification Ye Zhang, Byron C. Wallace International Joint Conference on Natural Language Processing (IJCNLP), 253--263, 2017.
  3. A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation Gaurav Singh, Iain Marshall, James Thomas, John Shawe-Taylor, Byron C. Wallace International Conference on Information and Knowledge Management (CIKM), 1519--1528, 2017.
  4. Quantifying Mental Health from Social Media with Neural User Embeddings Silvio Amir, Glen Coppersmith, Paula Carvalho, Mario J. Silva, Byron C. Wallace Proceedings of Machine Learning in Health Care (MLHC), 306--321, 2017.
  5. Automating Biomedical Evidence Synthesis: RobotReviewer Iain Marshall, Jo{\"e}l Kuiper, Edward Banner, Byron C. Wallace Proceedings of the Association for Computational Linguistics (ACL), System Demonstrations, 7--12, 2017.
  6. Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization Ye Zhang, Matthew Lease, Byron C. Wallace Proceedings of the Association for Computational Linguistics (ACL), 155--160, 2017.
  7. Aggregating and Predicting Sequence Labels from Crowd Annotations An Thanh Nguyen, Byron C. Wallace, Junyi Jessy Li, Ani Nenkova, Matthew Lease Proceedings of the Association for Computational Linguistics (ACL), 299--309, 2017.
  8. Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness Zhiguo Yu, Byron C. Wallace, Todd Johnson, Trevor Cohen Proceedings of MEDINFO, 657 -- 661, 2017.
  9. PheKnow–Cloud: A Tool for Evaluating High-Throughput Phenotype Candidates using Online Medical Literature Jette Henderson, Ryan Bridges, Joyce C. Ho, Byron C. Wallace, Joydeep Ghosh Proceedings of the AMIA Joint Summits on Translational Science, 149 -- 157, 2017. Recipient of the 2017 AMIA Distinguished Clinical Research Informatics Paper Award.
  10. Active Discriminative Text Representation Learning Ye Zhang, Matthew Lease, Byron C. Wallace Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 3386--3392, 2017.
  1. 2016
  2. Rationale-Augmented Convolutional Neural Networks for Text Classification Ye Zhang, Iain J. Marshall, Byron C. Wallace Proceedings of Empirical Methods in Natural Language Processing (EMNLP), 795--804, 2016.
  3. Using Electronic Medical Records and Physician Data to Improve Information Retrieval for Evidence-Based Care Mengqi Jin, Hongli Li, Chistopher Schmid, Byron C. Wallace Proceedings of the International Conference on Healthcare Informatics (ICHI), 61--64, 2016.
  4. Modelling Context with User Embeddings for Sarcasm Detection in Social Media Silvio Moreira, Byron C. Wallace, Hao Lyu, Paula Carvalho, Mário J. Gaspar da Silva Proceedings of the Conference on Computational Natural Language Learning (CoNLL), 167--177, 2016.
  5. A Correlated Worker Model for Grouped, Imbalanced and Multitask Data An T. Nguyen, Byron C. Wallace, Matthew Lease Proceedings of The Conference on Uncertainty in Artificial Intelligence (UAI), 537--546, 2016.
  6. Probabilistic Modeling for Crowdsourcing Partially-Subjective Ratings An T. Nguyen, Matthew Halpern, Byron C. Wallace, Matthew Lease Proceedings of The Conference on Human Computation and Crowdsourcing (HCOMP), 149--158, 2016.
  7. MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification Ye Zhang, Stephen Roller, Byron C. Wallace Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL), 1522--1527, 2016.
  1. 2015
  2. Combining Crowd and Expert Labels Using Decision Theoretic Active Learning An T. Nguyen, Byron C. Wallace, Matthew Lease AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 120--129, 2015.
  3. Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment Byron C. Wallace, Do Kook Choe, Eugene Charniak Proceedings of the Association for Computational Linguistics (ACL), 1035--1044, 2015.
  4. Graph-Sparse LDA: a topic model with structured sparsity Finale Doshi-Velez, Byron C. Wallace, Ryan P. Adams Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2575--2581, 2015.
  1. 2014
  2. Automating Risk of Bias Assessment for Clinical Trials Iain J. Marshall, Jo{\"e}l Kuiper, Byron C. Wallace Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Health Informatics (BCB), 88--95, 2014. Selected for inclusion in a special issue of the IEEE Journal of Biomedical and Health Informatics.
  3. Humans Require Context to Infer Ironic Intent (so Computers Probably do, too) Byron C. Wallace, Do Kook Choe, Laura Kertz, Eugene Charniak Proceedings of the Association for Computational Linguistics (ACL), 512--516, 2014.
  4. Spa: a Web-Based Viewer for Text Mining in Evidence Based Medicine Jo{\"e}l Kuiper, Iain J. Marshall, Byron C. Wallace, Morris A. Swertz Proceedings of the European Conference on Machine Learning (ECML), 452--455, 2014.
  5. Discovering Better AAAI Keywords via Clustering with Community-sourced Constraints Kelly H. Moran, Byron C. Wallace, Carla E. Brodley Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 1265--1271, 2014.
  6. Identifying Differences in Physician Communication Styles with a Log-Linear Transition Component Model Byron C. Wallace, Issa J. Dahabreh, Thomas A. Trikalinos, M. Barton Laws, Ira B. Wilson, Eugene Charniak Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 1314--1320, 2014.
  1. 2013
  2. A Generative Joint, Additive, Sequential Model of Topics and Speech Acts in Patient-Doctor Communication Byron C. Wallace, Thomas A Trikalinos, M. Barton Laws, Ira B. Wilson, Eugene Charniak Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 1765--1775, 2013.
  1. 2012
  2. Multiple Narrative Disentanglement: Unraveling Infinite Jest Byron C. Wallace Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), 1--10, 2012.
  3. Deploying an Interactive Machine Learning System in an Evidence-Based Practice Center: abstrackr Byron C. Wallace, Kevin Small, Carla E. Brodley, Joseph Lau, Thomas A. Trikalinos Proceedings of the ACM SIGHIT International Health Informatics Symposium, 819--824, 2012.
  4. Class Probability Estimates are Unreliable for Imbalanced Data (and How to Fix Them) Byron C. Wallace, Issa J. Dahabreh Proceedings of the International Conference on Data Mining (ICDM), 695--704, 2012. Selected as one of the `best of ICDM-2012'.
  1. 2011
  2. Class Imbalance, Redux Byron C. Wallace, K. Small, Carla E. Brodley, Thomas A. Trikalinos Proceedings of the International Conference on Data Mining (ICDM), 754--763, 2011.
  3. Who Should Label What? Instance Allocation in Multiple Expert Active Learning Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos Proceedings of the International Conference on Data Mining (SDM), 176-187, 2011.
  4. The Constrained Weight Space SVM: Learning with Ranked Features Kevin Small, Byron C. Wallace, Carla E. Brodley, Thomas A. Trikalinos Proceedings of the International Conference on Machine Learning (ICML), 754--763, 2011.
  1. 2010
  2. Active Learning for Biomedical Citation Screening Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD), 173--182, 2010.
  3. Modeling Annotation Time to Reduce Workload in Comparative Effectiveness Reviews Byron C. Wallace, Kevin Small, Carla E. Brodley, Joseph Lau, Thomas A. Trikalinos Proceedings of the 1st ACM International Health Informatics Symposium (IHI), 28--35, 2010.

Journal Articles

  1. 2024
  2. Artificial intelligence in food and nutrition evidence: The challenges and opportunities Regan L Bailey, Amanda J MacFarlane, Martha S Field, Ilias Tagkopoulos, Sergio E Baranzini, Kristen M Edwards, Christopher J Rose, Nicholas J Schork, Akshat Singhal, Byron C Wallace, others PNAS nexus, 3(12), pgae461, 2024.
  3. Do Multi-Document Summarization Models Synthesize? Jay DeYoung, Stephanie C. Martinez, Iain J. Marshall, Byron C. Wallace Transactions of the Association for Computational Linguistics (TACL), 2024.
  4. Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness Gongbo Zhang, Qiao Jin, Denis Jered McInerney, Yong Chen, Fei Wang, Curtis L Cole, Qian Yang, Yanshan Wang, Bradley A Malin, Mor Peleg, others Journal of Biomedical Informatics, 153, 104640, 2024.
  5. Question answering systems for health professionals at the point of care: A systematic review Gregory Kell, Angus Roberts, Serge Umansky, Linglong Qian, Davide Ferrari, Frank Soboczenski, Byron C Wallace, Nikhil Patel, Iain J Marshall Journal of the American Medical Informatics Association, 31, 1009--1024, 2024.
  1. 2022
  2. In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving Iain J Marshall, Thomas A Trikalinos, Frank Soboczenski, Hye Sun Yun, Gregory Kell, Rachel Marshall, Byron C Wallace Journal of Clinical Epidemiology, 2022.
  3. Accuracy and Efficiency of Machine Learning–Assisted Risk-of-Bias Assessments in ).replace("''", Real-World'' Systematic Reviews: A Noninferiority Randomized Controlled Trial Anneliese Arno, James Thomas, Byron C. Wallace, Iain J Marshall, Joanne E McKenzie, Julian H Elliott Annals of Internal Medicine, 2022.
  1. 2021
  2. State of the evidence: a survey of global disparities in clinical trials Iain J Marshall, Veline L{\textquoteright}Esperance, Rachel Marshall, James Thomas, Anna Noel-Storr, Frank Soboczenski, Benjamin Nye, Ani Nenkova, Byron C Wallace BMJ Global Health, 6(1), 2021.
  3. Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve Oshin Agarwal, Yinfei Yang, Byron C. Wallace, Ani Nenkova Computational Linguistics, 47(1), 117-140, 2021.
  1. 2020
  2. Predicting Unplanned Readmissions Following a Hip or Knee Arthroplasty: Retrospective Observational Study Ramin Mohammadi, Sarthak Jain, Amir T Namin, Melissa Scholem Heller, Ramya Palacholla, Sagar Kamarthi, Byron C. Wallace JMIR Medical Informatics, 8(11), e19761, 2020.
  3. Trialstreamer: A living, automatically updated database of clinical trial reports Iain J Marshall, Benjamin Nye, Joël Kuiper, Anna Noel-Storr, Rachel Marshall, Rory Maclean, Frank Soboczenski, Ani Nenkova, James Thomas, Byron C Wallace Journal of the American Medical Informatics Association, 27(12), 1903-1912, 2020.
  4. Semi-Automated Evidence Synthesis in Health Psychology: Current Methods and Future Prospects Iain J. Marshall, Blair T. Johnson, Zigeng Wang, Sanguthevar Rajasekaran, Byron C. Wallace Health Psychology Review, 14(1), 145--158, 2020.
  1. 2019
  2. Toward systematic review automation: a practical guide to using machine learning tools in research synthesis Iain J. Marshall, Byron C. Wallace Systematic Reviews, 8(19), 2019.
  3. Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study Frank Soboczenski, Thomas A. Trikalinos, Joël Kuiper, Randolph G. Bias, Byron C. Wallace, Iain J. Marshall BMC Medical Informatics and Decision Making, 19, 2019.
  4. Rapid Reviews may Produce Different Results to Systematic Reviews: A Metaepidemiological Study Iain J. Marshall, Rachel Marshall, Byron C. Wallace, Jon Brassey, James Thomas Journal of Clinical Epidemiology, 109, 30--41, 2019.
  1. 2018
  2. PIVET: A Scaled Phenotype Evidence Generation Framework using Online Medical Literature Jette Henderson, Junyuan Ke, Joyce C. Ho, Joydeep Ghosh, Byron C. Wallace Journal of Medical Internet Research (JMIR), 20, 2018.
  3. Machine learning for identifying Randomized Controlled Trials: An evaluation and practitioner's guide Iain J. Marshall, Anna Noel-Storr, Joël Kuiper, James Thomas, Byron C. Wallace Research Synthesis Methods, 1--12, 2018.
  1. 2017
  2. An Exploration of Crowdsourcing Citation Screening for Systematic Reviews Michael L. Mortensen, Gaelen P. Adam, Thomas A. Trikalinos, Tim Kraska, Byron C. Wallace Research Synthesis Methods, 8(3), 366--386, 2017.
  3. Living Systematic Reviews: 2. Combining Human and Machine Effort James Thomas, Anna Noel-Storr, Iain Marshall, Byron C. Wallace, Steven McDonald, Chris Mavergames, Paul Glasziou, Ian Shemilt, Anneliese Synnot, Tari Turner, others Journal of Clinical Epidemiology, 31-37, 2017.
  4. Neural Information Retrieval: At the End of the Early Years Kezban Dilek Onal, Ye Zhang, Ismail Sengor Altingovde, Md Mustafizur Rahman, Pinar Karagoz, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen, Dan Xu, Byron C.\ Wallace, Maarten de Rijke, Matthew Lease Information Retrieval, 1--72, 2017.
  5. Identifying Reports of Randomized Controlled Trials (RCTs) via a Hybrid Machine Learning and Crowdsourcing Approach Byron C. Wallace, Anna Noel-Storr, Iain J. Marshall, Aaron M. Cohen, Neil R. Smalheiser, James Thomas Journal of the American Medical Informatics Association (JAMIA), 1165--1168, 2017.
  6. OpenMEE: Intuitive, open-source software for meta-analysis in ecology and evolutionary biology Byron C. Wallace, Marc J. Lajeunesse, George Dietz, Issa J. Dahabreh, Thomas A. Trikalinos, Christopher H. Schmid, Jessica Gurevitch Methods in Ecology and Evolution, 8, 941--947, 2017.
  1. 2016
  2. Evaluating Data Abstraction Assistant, a novel software application for data abstraction during systematic reviews: protocol for a randomized controlled trial Ian J Saldanha, Christopher H Schmid, Joseph Lau, Kay Dickersin, Jesse A Berlin, Jens Jap, Bryant T Smith, Simona Carini, Wiley Chan, Berry De Bruijn, others Systematic reviews, 5(1), 196, 2016.
  3. Characterizing the (Perceived) Newsworthiness of Health Science Articles: A Data-Driven Approach Ye Zhang, Erin Willis, Michael J Paul, No{\'e}mie Elhadad, Byron C Wallace JMIR Medical Informatics, 4(3), e27, 2016.
  4. Extracting PICO Sentences from Clinical Trial Reports using Supervised Distant Supervision Byron C. Wallace, Jo{{\"e}}l Kuiper, Aakash Sharma, Mingxi (Brian) Zhu, Iain Marshall Journal of Machine Learning Research, 17(132), 1-25, 2016.
  5. Improving the Utility of MeSH Terms using the TopicalMeSH Representation Zhiguo Yu, Elmer Bernstam, Trevor Cohen, Byron C. Wallace, Todd R. Johnson Journal of Biomedical Informatics, 61, 77--86, 2016.
  6. RobotReviewer: Evaluation of a System for Automatically Assessing Bias in Clinical Trials Iain J. Marshall, Joël Kuiper, Byron C. Wallace Journal of the American Medical Informatics Association (JAMIA), 23(1), 193--201, 2016.
  1. 2015
  2. Automating Risk of Bias Assessment for Clinical Trials Iain J. Marshall, Joël Kuiper, Byron C. Wallace Journal of Biomedical and Health Informatics (JBHI), 19(4), 1406--1412, 2015. (An invited journal version of our 2014 ACM-BCB paper of the same the title.)
  1. 2014
  2. A Large-Scale Quantitative Analysis of Latent Factors and Sentiment in Online Doctor Reviews Byron C. Wallace, Michael J. Paul, Urmimala Sarkar, Thomas A. Trikalinos, Mark Dredze Journal of the American Medical Informatics Association (JAMIA), 21, 1098--1103, 2014.
  3. Automatically Annotating Topics in Transcripts of Patient-Provider Interactions via Machine Learning Byron C. Wallace, M. Barton Laws, Kevin Small, Ira B. Wilson, Thomas A. Trikalinos Medical Decision Making, 34(4), 503--512, 2014. Highlighted in an editorial piece entitled ).replace("''", From Text Tagging to Decision Support'' by HP Lehmann, MDM, 2014 ().
  4. Improving Class Probability Estimates for Imbalanced Data Byron C. Wallace, Issa J. Dahabreh Knowledge and Information Systems (KAIS), 41, 33--52, 2014.
  1. 2013
  2. Modernizing the systematic review process to inform comparative effectiveness: tools and methods Byron C. Wallace, Issa J. Dahabreh, Chistopher H. Schmid, Joseph Lau, Thomas A. Trikalinos Journal of Comparative Effectiveness Research, 2(3), 273--282, 2013.
  3. Computational irony: A survey and new perspectives Byron C. Wallace Artificial Intelligence Review, 43(4), 1--17, 2013.
  1. 2012
  2. Toward Modernizing the Systematic Review Pipeline in Genetics: Efficient Updating via Data Mining Byron C. Wallace, Kevin Small, Carla E. Brodley, Joseph Lau, Christopher H. Schmid, Lars Bertram, Christina M. Lill, Joshua T. Cohen, Thomas A. Trikalinos Genetics in Medicine, 14(7), 663--669, 2012.
  3. Closing the Gap between Methodologists and End-Users: R as a Computational Back-End Byron C. Wallace, Issa J. Dahabreh, Thomas A. Trikalinos, Joseph Lau, Paul Trow, Christopher H. Schmid Journal of Statistical Software, 49(5), 1--15, 2012.
  4. Challenges and Opportunities in Applied Machine Learning Carla E. Brodley, Umaa Rebbapragada, Kevin Small, Byron C. Wallace Artificial Intelligence Magazine, 33(1), 11--24, 2012.
  1. 2011
  2. Single Cell Time-resolved Quorum Responses Reveal Dependence on Cell Density and Configuration RD Whitaker, S Pember, BC Wallace, CE Brodley, DR Walt Journal of Biological Chemistry, 286(24), 21623--21632, 2011.
  1. 2010
  2. Semi-Automated Screening of Biomedical Citations for Systematic Reviews Byron C. Wallace, Thomas A. Trikalinos, Joseph Lau, Carla E. Brodley, Christopher H. Schmid BMC Bioinformatics, 11(1), 55+, 2010.
  3. The COPD Genetic Association Compendium: A Comprehensive Online Database of COPD Genetic Associations PJ Castaldi, MH Cho, M Cohn, F Langerman, S Moran, N Tarragona, H Moukhachen, R Venugopal, D Hasimja, E Kao, BC Wallace, CP Hersh, S Bagade, L Bertram, EK Silverman, TA Trikalinos Human Molecular Genetics, 19(3), 526--534, 2010.
  1. 2009
  2. Meta-Analyst: Software for Meta-analysis of Binary, Continuous and Diagnostic Data Byron C. Wallace, Christopher H. Schmid, Joseph Lau, Thomas A. Trikalinos BMC Medical Research Methodology, 9(1), 80+, 2009.

Workshop & Symposium Papers

  1. 2024
  2. Open (Clinical) LLMs are Sensitive to Instruction Phrasings Alberto Mario Ceballos-Arroyo, Monica Munnangi, Jiuding Sun, Karen Zhang, Jered McInerney, Byron C. Wallace, Silvio Amir Proceedings of the BioNLP Workshop, 2024.
  3. How Much Annotation is Needed to Compare Summarization Models? Chantal Shaib, Joe Barrow, Alexa Siu, Byron Wallace, Ani Nenkova Proceedings of the Workshop of HCI + NLP, 2024.
  1. 2022
  2. Overview of MSLR2022: A Shared Task on Multi-document Summarization for Literature Reviews Lucy Lu Wang, Jay DeYoung, Byron C. Wallace Proceedings of the Third Workshop on Scholarly Document Processing, 175--180, 2022.
  3. Learning to Ask Like a Physician Eric Lehman, Vladislav Lialin, Katelyn Edelwina Legaspi, Anne Janelle Sy, Patricia Therese Pile, Nicole Rose Alberto, Richard Raymund Ragasa, Corinna Victoria Puyat, Marianne Katharina Tali{\~n}o, Isabelle Rose Alberto, Pia Gabrielle Alfonso, Dana Moukheiber, Byron C. Wallace, Anna Rumshisky, Jennifer Liang, Preethi Raghavan, Leo Anthony Celi, Peter Szolovits Proceedings of the 4th Clinical Natural Language Processing Workshop, 74--86, 2022.
  4. Intermediate Entity-based Sparse Interpretable Representation Learning Diego Garcia-Olano, Yasumasa Onoe, Joydeep Ghosh, Byron C. Wallace Proceedings of the BlackboxNLP Workshop at EMNLP, 2022.
  1. 2021
  2. What Would it Take to get Biomedical QA Systems into Practice? Gregory Kell, Iain Marshall, Byron C. Wallace, Andre Jaun Proceedings the Workshop on Machine Reading for Question Answering (MRQA) at EMNLP, 2021.
  1. 2020
  2. Evidence Inference 2.0: More Data, Better Models Jay DeYoung, Eric Lehman, Benjamin Nye, Iain Marshall, Byron C. Wallace Proceedings of BioNLP; co-located with the Association for Computational Linguistics (ACL), 2020.
  1. 2019
  2. Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence Soham Parikh, Elizabeth Conrad, Oshin Agarwal, Iain Marshall, Byron C. Wallace, Ani Nenkova Workshop on extracting structured knowledge from scientific publications (ESSP); co-located with Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2019.
  3. An Analysis of Attention over Clinical Notes for Predictive Tasks Sarthak Jain, Ramin Mohammadi, Byron C.\ Wallace The 2nd Clinical Natural Language Processing Workshop; co-located with Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2019.
  4. MASH: software tools for developing interactive and transparent machine learning systems An Thanh Nguyen, Matthew Lease, Byron C.\ Wallace Proceedings of ACM IUI Workshop on Explainable Smart Systems (ExSS), 2019.
  1. 2017
  2. Detecting Twitter posts with Adverse Drug Reactions using Convolutional Neural Networks Sarthak Jain, Xun Peng, Byron C. Wallace Proceedings of the Social Media Mining for Health Research and Applications Workshop co-located with the American Medical Informatics Association Annual Symposium (AMIA), 72--75, 2017.
  3. Identifying Diagnostic Test Accuracy Publications using a Deep Model Gaurav Singh, Iain Marshall, James Thomas, Byron C. Wallace CLEF eHealth, 2017.
  1. 2016
  2. Leveraging Coreference to Identify Arms in Medical Abstracts: An Experimental Study Elisa Ferracane, Iain Marshall, Byron C. Wallace, Katrin Erk The International Workshop on Health Text Mining and Information Analysis at EMNLP, 2016.
  3. Retrofitting Word Vectors of MeSH Terms to Improve Semantic Similarity Measures Zhiguo Yu, Trevor Cohen, Todd R. Johnson, Byron C. Wallace, Elmer Bernstam The International Workshop on Health Text Mining and Information Analysis at EMNLP, 2016.
  4. Crowdsourcing Information Extraction for Biomedical Systematic Reviews Yalin Sun, Shengwei Wang, Pengxiang Cheng, Hao Lyu, Iain Marshall, Byron C. Wallace Human Computation and Crowdsourcing (HCOMP) Works-in-Progress, 2016.
  5. Automated Verification of Phenotypes using PubMed Ryan Bridges, Jette Henderson, Joyce Ho, Byron C Wallace, Joydeep Ghosh Proceedings of the Workshop on Methods and Applications in Healthcare Analytics at ACM-BCB, 2016.
  6. Systematic Review is e-Discovery in Doctor's Clothing Matthew Lease, Cormack V. Gordon, An Thanh Nguyen, Thomas A. Trikalinos, Byron C. Wallace Proceedings of the Medical Information Retrieval (MedIR) Workshop at the International ACM SIGIR Conference on Research and Development in Information Retrieval, 2016.
  1. 2015
  2. Healthcare Data Analytics Challenge Yu Zhiguo, Byron C. Wallace, Todd R. Johnson Proceedings of the International Conference on Healthcare Informatics (ICHI), 2015. (Describes our submission to the challenge, which won first place.)
  3. What Predicts Media Coverage of Health Science Articles? Byron C. Wallace, Michael J. Paul, Noemie Elhadad Proceedings of the International Workshop on the World Wide Web and Public Health Intelligence (W3PHI), 2015.
  1. 2013
  2. Active Literature Discovery for Scoping Evidence Reviews: How Many Needles are There? Byron C. Wallace, Issa J. Dahabreh, Kelly H. Moran, Carla E. Brodley, Thomas A. Trikalinos Proceedings of the KDD Workshop on Data Mining for Healthcare (KDD-DMH), 2013.
  3. What Affects Patient (Dis)satisfaction? Analyzing Online Doctor Ratings with a Joint Topic-Sentiment Model Michael J. Paul, Byron C. Wallace, Mark Dredze Proceedings of the AAAI Workshop on Expanding the Boundaries of Health Informatics Using AI (HIAI), 2013.

Book Chapters

  1. 2022
  2. Intelligent Agents and Dialog Systems Timothy Bickmore, Byron C. Wallace Intelligent Systems in Medicine and Health: The Role of AI, 2022.
  1. 2013
  2. Modernizing Evidence Synthesis for Evidence-Based Medicine Byron C. Wallace, Issa J. Dahabreh, Christopher H. Schmid, Joseph Lau, Thomas A. Trikalinos Clinical Decision Support (Second Edition), 2013.

Commentaries & Editorials

  1. 2019
  2. Invited Early Career Spotlight Extended Abstract: What Does the Evidence Say? Models to Help Make Sense of the Biomedical Literature Byron C. Wallace International Joint Conference on Artificial Intelligence, 6416--6420, 2019.
  1. 2015
  2. Editorial: Special Issue on Machine Learning for Health and Medicine Jenna Wiens, Byron C. Wallace Machine Learning Journal, 1--3, 2015.
  3. Invited Response: Using Text Mining for Study identification in Systematic Reviews: a Systematic Review of Current Approaches Byron C. Wallace, Iain J. Marshall Cochrane Methods, 2015.
  1. 2014
  2. \#CochraneTech: Technology and the Future of Systematic Reviews Julian Elliott, Ida Sim, Jessica Thomas, Nancy Owens, Gordon Dooley, Jacob Riis, Byron Wallace, James Thomas, Anna Noel-Storr, Gabriel Rada, Caroline Struthers, Tracey Howe, Harriet MacLehose, Linn Brandt, Ilkka Kunnamo, Chris Mavergames The Cochrane Library, 2014.
  1. 2012
  2. Invited Response: Applications of Text Mining Within Systematic Reviews Byron C. Wallace, Thomas A. Trikalinos Cochrane Methods, 2012.