A machine learning approach to predicting clinical trajectories in bipolar disorder

Psychiatry Research, vol. 359, pp. 117009

Authors 7

1. Ovinuchi Ejiohuo corresponding

   Poznan University of Medical Sciences · University of Maryland Global Campus

   Affiliation as printed

   Department of Biology, University of Maryland Global Campus, UMGC in Europe, Poznan, Poland; Doctoral School, Poznan University of Medical Sciences, 60-812 Poznan, Poland. Electronic address: ovinuchi.ejiohuo@gmail.com

2. Frances Nkechi Adiukwu

   University of Port Harcourt · University of Port Harcourt Teaching Hospital

   Affiliation as printed

   Department of Mental Health, College of Health Sciences, University of Port Harcourt, Port Harcourt, Rivers State, Nigeria; Department of Neuropsychiatry, University of Port Harcourt Teaching Hospital, Port Harcourt, Rivers State, Nigeria

3. Adeboye Olakunle Bamgboye

   University of Minnesota

   Affiliation as printed

   Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States; Center for Orphan Drug Research, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States

4. Samson O. Folami Aachen Department of Immunology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Immunology, Leiden University Medical Center, Leiden, the Netherlands

5. Emmanuel Aniekan Essien

   Federal Neuro-Psychiatric Hospital, Calabar

   Affiliation as printed

   Department of Clinical Services, Federal Neuropsychiatry Hospital, Calabar, Cross River, Nigeria

6. Gabriel Osagiede

   Wrexham University

   Affiliation as printed

   Department of Health Management, Wrexham University, LL11 2AW Wrexham, United Kingdom

7. Olubusola O. Olaleye

   University of Lagos

   Affiliation as printed

   Department of Pharmacognosy, Faculty of Pharmacy, College of Medicine Campus, University of Lagos, Lagos State, Nigeria