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Journal of Child and Adolescent Psychopharmacology|June 15, 2022
A Characterization of the Clinical Global Impression Scale Thresholds in the Treatment of Adolescent Depression Across Multiple Rating ScalesCarl Y Zhang, Jennifer L Vande Voort, Deniz Yuruk, et al.Frontiers in Pharmacology|October 20, 2022
Network science approach elucidates integrative genomic-metabolomic signature of antidepressant response and lifetime history of attempted suicide in adults with major depressive disorderCaroline W Grant, Angelina R Wilton, Rima Kaddurah-Daouk, et al.Journal of Personalized Medicine|March 25, 2022
Multi-Omics Characterization of Early- and Adult-Onset Major Depressive DisorderCaroline W Grant, Erin F Barreto, Rakesh Kumar, et al.Journal of Child Psychology and Psychiatry, and Allied Disciplines|March 15, 2022
Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressantsArjun P Athreya, Jennifer L Vande Voort, Julia Shekunov, et al.Clinical and Translational Science|October 15, 2024
Pharmacogenomic augmented machine learning in electronic health record alerts: A health system-wide usability survey of cliniciansCaroline W Grant, Jean Marrero-Polanco, Jeremiah B Joyce, et al.JAMA Network Open|December 15, 2025
Feasibility of Digital Augmentation of Parent-Child Interaction Therapy: A Randomized Clinical TrialMagdalena Romanowicz, Maria T Saliba, Angelina R Wilton, et al.Translational Psychiatry|October 8, 2021
Multi-omics driven predictions of response to acute phase combination antidepressant therapy: a machine learning approach with cross-trial replicationJeremiah B Joyce, Caroline W Grant, Duan Liu, et al.Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology|January 16, 2021
Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settingsArjun P Athreya, Tanja Brückl, Elisabeth B Binder, et al.Arthritis Care & Research|December 13, 2021
Toward Individualized Prediction of Response to Methotrexate in Early Rheumatoid Arthritis: A Pharmacogenomics-Driven Machine Learning ApproachElena Myasoedova, Arjun P Athreya, Cynthia S Crowson, et al.Clinical and Translational Science|July 10, 2026
Machine Learning With Genetic and Clinical Data to Predict Ischemic Outcomes After PCICaroline W Grant, Brenden S Ingraham, Ryan J Lennon, et al.Pageof 6