Articles with public access mandates - John LalorLearn more
Not available anywhere: 1
Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines
JP Lalor, A Abbasi, K Oketch, Y Yang, N Forsgren
ACM Transactions on Information Systems, 2024
Mandates: US National Science Foundation
Available somewhere: 13
Building an evaluation scale using item response theory
JP Lalor, H Wu, H Yu
Proceedings of the conference on empirical methods in natural language …, 2016
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Evaluation examples are not equally informative: How should that change NLP leaderboards?
P Rodriguez, J Barrow, AM Hoyle, JP Lalor, R Jia, J Boyd-Graber
Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021
Mandates: US National Science Foundation
Benchmarking intersectional biases in NLP
JP Lalor, Y Yang, K Smith, N Forsgren, A Abbasi
Proceedings of the 2022 conference of the North American chapter of the …, 2022
Mandates: US National Science Foundation
Learning latent parameters without human response patterns: Item response theory with artificial crowds
JP Lalor, H Wu, H Yu
Proceedings of the Conference on Empirical Methods in Natural Language …, 2019
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Understanding deep learning performance through an examination of test set difficulty: A psychometric case study
JP Lalor, H Wu, T Munkhdalai, H Yu
Proceedings of the Conference on Empirical Methods in Natural Language …, 2018
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Detecting hypoglycemia incidents reported in patients’ secure messages: using cost-sensitive learning and oversampling to reduce data imbalance
J Chen, J Lalor, W Liu, E Druhl, E Granillo, VG Vimalananda, H Yu
Journal of medical Internet research 21 (3), e11990, 2019
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Citation analysis with neural attention models
T Munkhdalai, JP Lalor, H Yu
Proceedings of the Seventh International Workshop on Health Text Mining and …, 2016
Mandates: US National Institutes of Health
Improving electronic health record note comprehension with NoteAid: randomized trial of electronic health record note comprehension interventions with crowdsourced workers
JP Lalor, B Woolf, H Yu
Journal of medical Internet research 21 (1), e10793, 2019
Mandates: US National Institutes of Health, US Department of Veterans Affairs
ComprehENotes, an instrument to assess patient reading comprehension of electronic health record notes: development and validation
JP Lalor, H Wu, L Chen, KM Mazor, H Yu
Journal of medical Internet research 20 (4), e139, 2018
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Dynamic data selection for curriculum learning via ability estimation
JP Lalor, H Yu
Proceedings of the conference on empirical methods in natural language …, 2020
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Constructing a psychometric testbed for fair natural language processing
A Abbasi, D Dobolyi, JP Lalor, RG Netemeyer, K Smith, Y Yang
Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021
Mandates: US National Science Foundation
Evaluating the effectiveness of NoteAid in a community hospital setting: randomized trial of electronic health record note comprehension interventions with patients
JP Lalor, W Hu, M Tran, H Wu, KM Mazor, H Yu
Journal of medical Internet research 23 (5), e26354, 2021
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Evaluating the efficacy of NoteAid on EHR note comprehension among US Veterans through Amazon Mechanical Turk
JP Lalor, H Wu, KM Mazor, H Yu
International journal of medical informatics 172, 105006, 2023
Mandates: US National Institutes of Health, US Department of Veterans Affairs
Publication and funding information is determined automatically by a computer program