*Yuki Yamamoto1, Genichi Sugihara1, Masaaki Shimizu1, Takahiko Kawashima2, Ayumu Yamashita3,6, Yujiro Yoshihara2, Junichiro Yoshimoto3,8, Jun Miyata2,4, Toshiya Murai2, Mitsuo Kawato3,7, Ming-Chyi Huang9,10, Hidehiko Takahashi1,5
(1. Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan, 2. Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan, 3. Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institutes International (ATR), Kyoto, Japan, 4. Department of Psychiatry, Aichi Medical University, Aichi, Japan, 5. Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo, Japan, 6. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan, 7. XNef Incorporation, Kyoto, Japan, 8. Department of Biomedical Data Science, School of Medicine, Fujita Health University, Aichi, Japan, 9. Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan, 10. Department of Psychiatry, School of Medicine, Taipei Medical University, Taipei, Taiwan)
Keywords:substance-induced psychosis, methamphetamine-induced psychosis, schizophrenia, resting-state fMRI, machine learning
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