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Computer Science

D-Index
47
Citations
24398
World Ranking
6281
National Ranking
2808

Overview

Byron C. Wallace is affiliated with Northeastern University in the United States. Their research focuses primarily on computer science, with a specialization in artificial intelligence. They have contributed extensively to subfields including molecular biology, statistics, probability and uncertainty, health informatics, and general social sciences.

Their main research topics cover a range of areas related to text processing and machine learning, such as:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Healthcare
  • Text Readability and Simplification
  • Meta-analysis and Systematic Reviews
  • Artificial Intelligence in Healthcare and Education

Byron C. Wallace has published research in notable venues including:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • PubMed
  • Journal of the American Medical Informatics Association

Frequent collaborators include authors such as Iain Marshall, Ani Nenkova, Frank Soboczenski, Benjamin Nye, and James Thomas.

Among their recent publications are:

  • "Trialstreamer: A living, automatically updated database of clinical trial reports" (2020), Journal of the American Medical Informatics Association
  • "Predicting Unplanned Readmissions Following a Hip or Knee Arthroplasty: Retrospective Observational Study" (2020), JMIR Medical Informatics
  • "Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization" (2020), arXiv (Cornell University)
  • "Evaluating Factuality in Text Simplification" (2022), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • "The views of health guideline developers on the use of automation in health evidence synthesis" (2021), Systematic Reviews

Best Publications

  • A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence Classification

    Ye Zhang;Byron C. Wallace

  • 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

  • Attention is not Explanation.

    Sarthak Jain;Byron C. Wallace

  • Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data

    Byron C Wallace;Byron C Wallace;Christopher H Schmid;Joseph Lau;Thomas A Trikalinos

  • Deploying an interactive machine learning system in an evidence-based practice center: abstrackr

    Byron C. Wallace;Kevin Small;Carla E. Brodley;Joseph Lau

  • Toward systematic review automation: a practical guide to using machine learning tools in research synthesis

    Iain J. Marshall;Byron C. Wallace

  • ERASER: A Benchmark to Evaluate Rationalized NLP Models

    Jay DeYoung;Sarthak Jain;Nazneen Fatema Rajani;Eric Lehman

  • Semi-automated screening of biomedical citations for systematic reviews

    Byron C. Wallace;Byron C. Wallace;Thomas A. Trikalinos;Joseph Lau;Carla E. Brodley

  • OpenMEE : Intuitive, open-source software for meta-analysis in ecology and evolutionary biology

    Byron C. Wallace;Marc J. Lajeunesse;George Dietz;Issa J. Dahabreh

  • Machine learning for identifying Randomized Controlled Trials: An evaluation and practitioner's guide.

    Iain J. Marshall;Anna Noel-Storr;Joël Kuiper;James Thomas

  • Living systematic reviews: 2. Combining human and machine effort.

    James Thomas;Anna Noel-Storr;Iain Marshall;Byron Wallace

  • RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials

    Iain James Marshall;Joël Kuiper;Byron C. Wallace

  • Modelling Context with User Embeddings for Sarcasm Detection in Social Media

    Silvio Amir;Byron C. Wallace;Hao Lyu;Paula Carvalho

  • Class Imbalance, Redux

    Byron C. Wallace;Kevin Small;Carla E. Brodley;Thomas A. Trikalinos

  • A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature.

    Benjamin E. Nye;Junyi Jessy Li;Roma Patel;Yinfei Yang

  • Rationale-Augmented Convolutional Neural Networks for Text Classification

    Ye Zhang;Iain James Marshall;Byron C. Wallace

  • Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach

    Byron C. Wallace;Anna Noel-Storr;Iain James Marshall;Aaron M. Cohen

  • Neural information retrieval: at the end of the early years

    Kezban Dilek Onal;Kezban Dilek Onal;Ye Zhang;Ismail Sengor Altingovde;Md. Mustafizur Rahman

  • Humans Require Context to Infer Ironic Intent (so Computers Probably do, too)

    Byron C. Wallace;Do Kook Choe;Laura Kertz;Eugene Charniak

  • Active learning for biomedical citation screening

    Byron C. Wallace;Kevin Small;Carla E. Brodley;Thomas A. Trikalinos

  • Active discriminative text representation learning

    Ye Zhang;Matthew Lease;Byron C. Wallace

  • Extracting PICO sentences from clinical trial reports using supervised distant supervision

    Byron C. Wallace;Joël Kuiper;Aakash Sharma;Mingxi Zhu

  • Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

    Xiaochuang Han;Byron C. Wallace;Yulia Tsvetkov

Frequent Co-Authors

Ani Nenkova
Ani Nenkova Adobe Systems (United States)
Matthew Lease
Matthew Lease The University of Texas at Austin
Carla E. Brodley
Carla E. Brodley Northeastern University
Michael J. Paul
Michael J. Paul University of Colorado Boulder
Eugene Charniak
Eugene Charniak Brown University
Joydeep Ghosh
Joydeep Ghosh The University of Texas at Austin
Zachary C. Lipton
Zachary C. Lipton Carnegie Mellon University
Mário J. Silva
Mário J. Silva Instituto Superior Técnico
John Shawe-Taylor
John Shawe-Taylor University College London
Elmer V. Bernstam
Elmer V. Bernstam The University of Texas Health Science Center at Houston

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