{"title":"计算精神病学试验","authors":"Quentin J. M. Huys, Michael Browning","doi":"10.1038/s43588-025-00879-6","DOIUrl":null,"url":null,"abstract":"Computational psychiatry is increasingly delivering causal evidence by focusing on interventions research and clinical trials. Causal evidence could improve patient outcomes through improved precision, repurposing, novel interventions, scaling of psychotherapy and better translation to the clinic.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"5 10","pages":"841-843"},"PeriodicalIF":18.3000,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trials for computational psychiatry\",\"authors\":\"Quentin J. M. Huys, Michael Browning\",\"doi\":\"10.1038/s43588-025-00879-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computational psychiatry is increasingly delivering causal evidence by focusing on interventions research and clinical trials. Causal evidence could improve patient outcomes through improved precision, repurposing, novel interventions, scaling of psychotherapy and better translation to the clinic.\",\"PeriodicalId\":74246,\"journal\":{\"name\":\"Nature computational science\",\"volume\":\"5 10\",\"pages\":\"841-843\"},\"PeriodicalIF\":18.3000,\"publicationDate\":\"2025-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature computational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43588-025-00879-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-025-00879-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Computational psychiatry is increasingly delivering causal evidence by focusing on interventions research and clinical trials. Causal evidence could improve patient outcomes through improved precision, repurposing, novel interventions, scaling of psychotherapy and better translation to the clinic.
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