Joseph Mehltretter

According to our database, Joseph Mehltretter authored at least 4 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• 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

2019

Analysis of Features Selected by a Deep Learning Model for Differential Treatment Selection in Depression.

Joseph Mehltretter, Colleen Rollins, David Benrimoh, Robert Fratila, Kelly Perlman, Sonia Israel, Marc Miresco, Marina Wakid, Gustavo Turecki

Frontiers Artif. Intell., 2019

Big Data Analytics and AI in Mental Healthcare.

Ariel Rosenfeld, David Benrimoh, Caitrin Armstrong, Nykan Mirchi, Timothe Langlois-Therrien, Colleen Rollins, Myriam Tanguay-Sela, Joseph Mehltretter, Robert Fratila, Sonia Israel, Emily Snook, Kelly Perlman, Akiva Kleinerman, Bechara Saab, Mark Thoburn, Cheryl Gabbay, Amit Yaniv-Rosenfeld

CoRR, 2019