Adam Kapelner

According to our database, Adam Kapelner authored at least 11 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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.

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

CoRR, 2024

2023

Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies.

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

CoRR, 2023

2021

Evaluating the Effectiveness of Personalized Medicine With Software.

Adam Kapelner, Justin Bleich, Alina Levine, Zachary D. Cohen, Robert J. DeRubeis, Richard Berk

Frontiers Big Data, 2021

Editorial: ML and AI Safety, Effectiveness and Explainability in Healthcare.

David Benrimoh, Sonia Israel, Robert Fratila, Caitrin Armstrong, Kelly Perlman, Ariel Rosenfeld, Adam Kapelner

Frontiers Big Data, 2021

2020

The Bayesian Additive Regression Trees Formula for Safe Machine Learning-Based Intraocular Lens Predictions.

Gerald P. Clarke, Adam Kapelner

Frontiers Big Data, 2020

2018

Predicting Contextual Informativeness for Vocabulary Learning.

Adam Kapelner, Jeanine Soterwood, Shalev Nessaiver, Suzanne Adlof

IEEE Trans. Learn. Technol., 2018

2016

Predicting Individual Well-Being Through the Language of Social Media.

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

Proceedings of the Biocomputing 2016: Proceedings of the Pacific Symposium, 2016

2013

bartMachine: A Powerful Tool for Machine Learning.

Adam Kapelner, Justin Bleich

CoRR, 2013

Prediction with Missing Data via Bayesian Additive Regression Trees.

Adam Kapelner, Justin Bleich

CoRR, 2013

2012

Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets

Dana Chandler, Adam Kapelner

CoRR, 2012

New Insights from Coarse Word Sense Disambiguation in the Crowd.

Adam Kapelner, Krishna Kaliannan, Hansen Andrew Schwartz, Lyle H. Ungar, Dean P. Foster

Proceedings of the COLING 2012, 2012