Marshall, Iain J.

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

Marshall, I. J., & Wallace, B. C. (2019) · Systematic Reviews

Meta-analysis and systematic reviewsComputational and Text Analysis Methods

Cited by 638

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

Marshall, I. J., Noel‐Storr, A., Kuiper, J., Thomas, J., & Wallace, B. C. (2018) · Research Synthesis Methods

Meta-analysis and systematic reviewsInformation Retrieval and Search Behavior

Cited by 435

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

Marshall, I. J., Kuiper, J., & Wallace, B. C. (2016) · Journal of the American Medical Informatics Association

Meta-analysis and systematic reviewsComputational and Text Analysis Methods

Cited by 317

Machine learning reduced workload with minimal risk of missing studies: development and evaluation of a randomized controlled trial classifier for Cochrane Reviews

Thomas, J., McDonald, S., Noel-Storr, A., Shemilt, I., Elliott, J., Mavergames, C., & Marshall, I. J. (2021) · Journal of Clinical Epidemiology

Meta-analysis and systematic reviewsInformation Retrieval and Search Behavior

Cited by 253

Rationale-Augmented Convolutional Neural Networks for Text Classification

Zhang, Y., Marshall, I., & Wallace, B. C. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

Topic ModelingText and Document Classification Technologies

Cited by 249

A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature

Nye, B., Li, J. J., Patel, R., Yang, Y., Marshall, I., Nenkova, A., & Wallace, B. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Biomedical Text Mining and OntologiesMeta-analysis and systematic reviews

Cited by 224

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

Wallace, B. C., Noel-Storr, A., Marshall, I. J., Cohen, A. M., Smalheiser, N. R., & Thomas, J. (2017) · Journal of the American Medical Informatics Association

Meta-analysis and systematic reviewsBiomedical Text Mining and Ontologies

Cited by 186

Automating Biomedical Evidence Synthesis: RobotReviewer

Marshall, I., Kuiper, J., Banner, E., & Wallace, B. C. (2017) · Proceedings of ACL 2017, System Demonstrations

Meta-analysis and systematic reviewsBiomedical Text Mining and Ontologies

Cited by 96

Paragraph-level Simplification of Medical Texts

Devaraj, A., Marshall, I., Wallace, B., & Li, J. J. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Text Readability and SimplificationTopic Modeling

Cited by 79

Automating Risk of Bias Assessment for Clinical Trials

Marshall, I. J., Kuiper, J., & Wallace, B. C. (2015) · IEEE Journal of Biomedical and Health Informatics

Meta-analysis and systematic reviewsBiomedical Text Mining and Ontologies

Cited by 59

Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study

Soboczenski, F., Trikalinos, T. A., Kuiper, J., Bias, R. G., Wallace, B. C., & Marshall, I. J. (2019) · BMC Medical Informatics and Decision Making

Meta-analysis and systematic reviewsComputational and Text Analysis Methods

Cited by 53

Evidence inference 2.0: More data, better models.

DeYoung, J., Lehman, E., Nye, B., Marshall, I., & Wallace, B. C. (2020) · Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 49

Understanding Clinical Trial Reports: Extracting Medical Entities and Their Relations

Nye, B. E., DeYoung, J., Lehman, E., Nenkova, A., Marshall, I. J., & Wallace, B. C. (2020) · arXiv

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 15

A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation.

Singh, G., Marshall, I. J., Thomas, J., Shawe-Taylor, J., & Wallace, B. C. (2017) · Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 11