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For: Wu CS, Luedtke AR, Sadikova E, Tsai HJ, Liao SC, Liu CC, Gau SS, VanderWeele TJ, Kessler RC. Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia. JAMA Netw Open 2020;3:e1921660. [PMID: 32083693 DOI: 10.1001/jamanetworkopen.2019.21660] [Cited by in Crossref: 10] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 Wu CS, Yang AC, Chang SS, Chang CM, Liu YH, Liao SC, Tsai HJ. Validation of Machine Learning-Based Individualized Treatment for Depressive Disorder Using Target Trial Emulation. J Pers Med 2021;11:1316. [PMID: 34945788 DOI: 10.3390/jpm11121316] [Reference Citation Analysis]
2 Chekroud AM, Bondar J, Delgadillo J, Doherty G, Wasil A, Fokkema M, Cohen Z, Belgrave D, DeRubeis R, Iniesta R, Dwyer D, Choi K. The promise of machine learning in predicting treatment outcomes in psychiatry. World Psychiatry 2021;20:154-70. [PMID: 34002503 DOI: 10.1002/wps.20882] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
3 Nierenberg AA. Critical Problem Solving in the “Impossible Profession” of Psychiatry. Psychiatric Annals 2021;51:295-295. [DOI: 10.3928/00485713-20210608-02] [Reference Citation Analysis]
4 Rudolph KE, Díaz I, Luo SX, Rotrosen J, Nunes EV. Optimizing opioid use disorder treatment with naltrexone or buprenorphine. Drug Alcohol Depend 2021;228:109031. [PMID: 34534863 DOI: 10.1016/j.drugalcdep.2021.109031] [Reference Citation Analysis]
5 Amoretti S, Verdolini N, Mezquida G, Rabelo-da-Ponte FD, Cuesta MJ, Pina-Camacho L, Gomez-Ramiro M, De-la-Cámara C, González-Pinto A, Díaz-Caneja CM, Corripio I, Vieta E, de la Serna E, Mané A, Solé B, Carvalho AF, Serra M, Bernardo M. Identifying clinical clusters with distinct trajectories in first-episode psychosis through an unsupervised machine learning technique. Eur Neuropsychopharmacol 2021;47:112-29. [PMID: 33531261 DOI: 10.1016/j.euroneuro.2021.01.095] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 Bickman L. Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health. Adm Policy Ment Health 2020;47:795-843. [PMID: 32715427 DOI: 10.1007/s10488-020-01065-8] [Cited by in Crossref: 11] [Cited by in F6Publishing: 8] [Article Influence: 11.0] [Reference Citation Analysis]
7 Kessler RC, Bauer MS, Bishop TM, Demler OV, Dobscha SK, Gildea SM, Goulet JL, Karras E, Kreyenbuhl J, Landes SJ, Liu H, Luedtke AR, Mair P, McAuliffe WHB, Nock M, Petukhova M, Pigeon WR, Sampson NA, Smoller JW, Weinstock LM, Bossarte RM. Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System. Front Psychiatry 2020;11:390. [PMID: 32435212 DOI: 10.3389/fpsyt.2020.00390] [Cited by in Crossref: 10] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
8 Nierenberg AA. Precision Psychiatry and a Vision for the Future. Psychiatric Annals 2021;51:206-206. [DOI: 10.3928/00485713-20210409-01] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]