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Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions.

, , , , , , , , and . J. Am. Medical Informatics Assoc., 28 (6): 1225-1234 (2021)

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Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study., , , , and . CoRR, (2023)Challenges and opportunities of using reinforcement learning to optimize behavioral health interventions delivered via smartphones., , , , , , , , and . AMIA, AMIA, (2020)Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare., , , , , , , and . CoRR, (2024)Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions., , , , , , , , and . J. Am. Medical Informatics Assoc., 28 (6): 1225-1234 (2021)AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data., , , , , , and . CoRR, (2021)Development and Validation of a Survival Score for the Emergency Department in Singapore., , , and . AMIA, AMIA, (2021)Preface to the 1st International Workshop on Algorithmic Behavior Change Support., , , , , , , , , and 4 other author(s). PERSUASIVE (Adjunct), volume 3728 of CEUR Workshop Proceedings, page 1-7. CEUR-WS.org, (2024)Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques., , , , , , , , , and 1 other author(s). Artif. Intell. Medicine, (August 2023)Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies., , , , , , , and . J. Biomed. Informatics, (2022)Benchmarking Emergency Department Triage Prediction Models with Machine Learning and Large Public Electronic Health Records., , , , , , , , , and 3 other author(s). AMIA, AMIA, (2022)