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2020 – today
- 2024
[i5]David Benrimoh, Caitrin Armstrong, Joseph Mehltretter, Robert Fratila, Kelly Perlman, Sonia Israel, Adam Kapelner, Sagar V. Parikh, Jordan F. Karp, Katherine A. Heller, Gustavo Turecki:
Development and Validation of a Deep-Learning Model for Differential Treatment Benefit Prediction for Adults with Major Depressive Disorder Deployed in the Artificial Intelligence in Depression Medication Enhancement (AIDME) Study. CoRR abs/2406.04993 (2024)- 2023
- [i4]David Benrimoh, Akiva Kleinerman, Toshi A. Furukawa, Charles F. Reynolds III, Eric Lenze, Jordan F. Karp, Benoit H. Mulsant, Caitrin Armstrong, Joseph Mehltretter, Robert Fratila, Kelly Perlman, Sonia Israel, Myriam Tanguay-Sela, Christina Popescu, Grace Golden, Sabrina Qassim, Alexandra Anacleto, Adam Kapelner, Ariel Rosenfeld, Gustavo Turecki:
Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies. CoRR abs/2303.15202 (2023) - 2021
- [j4]Adam Kapelner
, Justin Bleich, Alina Levine, Zachary D. Cohen, Robert J. DeRubeis, Richard Berk:
Evaluating the Effectiveness of Personalized Medicine With Software. Frontiers Big Data 4: 572532 (2021) - [j3]David Benrimoh, Sonia Israel, Robert Fratila, Caitrin Armstrong, Kelly Perlman, Ariel Rosenfeld, Adam Kapelner:
Editorial: ML and AI Safety, Effectiveness and Explainability in Healthcare. Frontiers Big Data 4: 727856 (2021) - 2020
- [j2]Gerald P. Clarke, Adam Kapelner:
The Bayesian Additive Regression Trees Formula for Safe Machine Learning-Based Intraocular Lens Predictions. Frontiers Big Data 3: 572134 (2020)
2010 – 2019
- 2018
- [j1]Adam Kapelner, Jeanine Soterwood, Shalev Nessaiver, Suzanne Adlof:
Predicting Contextual Informativeness for Vocabulary Learning. IEEE Trans. Learn. Technol. 11(1): 13-26 (2018) - 2016
- [c2]H. Andrew Schwartz, Maarten Sap, Margaret L. Kern, Johannes C. Eichstaedt, Adam Kapelner, Megha Agrawal, Eduardo Blanco, Lukasz Dziurzynski, Gregory J. Park, David Stillwell, Michal Kosinski, Martin E. P. Seligman, Lyle H. Ungar:
Predicting Individual Well-Being Through the Language of Social Media. PSB 2016: 516-527 - 2013
- [i3]Adam Kapelner, Justin Bleich:
Prediction with Missing Data via Bayesian Additive Regression Trees. CoRR abs/1306.0618 (2013) - [i2]Adam Kapelner, Justin Bleich:
bartMachine: A Powerful Tool for Machine Learning. CoRR abs/1312.2171 (2013) - 2012
- [c1]Adam Kapelner, Krishna Kaliannan, Hansen Andrew Schwartz, Lyle H. Ungar, Dean P. Foster:
New Insights from Coarse Word Sense Disambiguation in the Crowd. COLING (Posters) 2012: 539-548 - [i1]Dana Chandler, Adam Kapelner:
Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets. CoRR abs/1210.0962 (2012)
Coauthor Index
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