Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study in...Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study investigates how artificial intelligence(AI)and machine learning(ML)can address key challenges in integrating pharmacogenomics(PGx)into psychiatric care.In this integration,AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions.AI-driven models integrating genomic,clinical,and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder.This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry,highlighting the importance of ethical considerations and the need for personalized treatment.Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care.Future research should focus on developing enhanced AI-driven predictive models,privacy-preserving data exchange,and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.展开更多
实现大数据基础上的精准医学目标,需要可靠的证据支持、信息技术和产品保障。本文介绍了国外较为成熟的临床决策支持产品:法国居里研究院的无缝信息产品和护理决策支持产品My cancer genome、IBM的Watson及相关的证据研究。建议我国借...实现大数据基础上的精准医学目标,需要可靠的证据支持、信息技术和产品保障。本文介绍了国外较为成熟的临床决策支持产品:法国居里研究院的无缝信息产品和护理决策支持产品My cancer genome、IBM的Watson及相关的证据研究。建议我国借鉴美国方式培养生物信息学高端人才、开放医疗数据共享、制定需求导向的研究战略,科学布局,建设生物信息学基础框架和癌症知识网络,推动基因组、蛋白质组等组学技术研究成果与临床电子病历系统的对接与融合。展开更多
文摘Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study investigates how artificial intelligence(AI)and machine learning(ML)can address key challenges in integrating pharmacogenomics(PGx)into psychiatric care.In this integration,AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions.AI-driven models integrating genomic,clinical,and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder.This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry,highlighting the importance of ethical considerations and the need for personalized treatment.Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care.Future research should focus on developing enhanced AI-driven predictive models,privacy-preserving data exchange,and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.
文摘实现大数据基础上的精准医学目标,需要可靠的证据支持、信息技术和产品保障。本文介绍了国外较为成熟的临床决策支持产品:法国居里研究院的无缝信息产品和护理决策支持产品My cancer genome、IBM的Watson及相关的证据研究。建议我国借鉴美国方式培养生物信息学高端人才、开放医疗数据共享、制定需求导向的研究战略,科学布局,建设生物信息学基础框架和癌症知识网络,推动基因组、蛋白质组等组学技术研究成果与临床电子病历系统的对接与融合。