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Journal of Medical Internet Research|June 7, 2015
A Scalable Framework to Detect Personal Health Mentions on TwitterZhijun Yin, Daniel Fabbri, S Trent Rosenbloom, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 21, 2022
Predicting Motor Responsiveness to Deep Brain Stimulation with Machine LearningKevin J Krause, Fenna Phibbs, Thomas Davis, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|June 2, 2018
Evaluating the Effectiveness of Auditing Rules for Electronic Health Record SystemsMonica Hedda, Bradley A Malin, Chao Yan, et al.
Proceedings of the ... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media|August 27, 2019
#PrayForDad: Learning the Semantics Behind Why Social Media Users Disclose Health InformationZhijun Yin, You Chen, Daniel Fabbri, et al.
Otolaryngology--Head and Neck Surgery : Official Journal of American Academy of Otolaryngology-Head and Neck Surgery|March 20, 2023
Objective Pharyngeal Phenotyping in Obstructive Sleep Apnea With High-Resolution ManometryDavid T Kent, William C Scott, Cheng Ye, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 10, 2016
Automated Classification of Consumer Health Information Needs in Patient Portal MessagesRobert M Cronin, Daniel Fabbri, Joshua C Denny, et al.
Proceedings of Spie--The International Society for Optical Engineering|March 9, 2026
Deep Learning for Brain Tumor ClassificationJustin S Paul, Andrew J Plassard, Bennett A Landman, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 9, 2017
Predicting Negative Events: Using Post-discharge Data to Detect High-Risk PatientsLina Sulieman, Daniel Fabbri, Fei Wang, et al.
Medrxiv : the Preprint Server for Health Sciences|February 14, 2024
Use of Noisy Labels as Weak Learners to Identify Incompletely Ascertainable Outcomes: A Feasibility Study with Opioid-Induced Respiratory DepressionAlvin D Jeffery, Daniel Fabbri, Ruth M Reeves, et al.
Heliyon|March 6, 2024
Use of noisy labels as weak learners to identify incompletely ascertainable outcomes: A Feasibility study with opioid-induced respiratory depressionAlvin D Jeffery, Daniel Fabbri, Ruth M Reeves, et al.
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