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Predicting antidepressant remission in late-life depression using polygenic risk scoring and machine learning models

Predicting antidepressant remission in late-life depression using polygenic risk scoring and machine learning models
使用多基因风险评分和机器学习模型预测晚年抑郁症的抗抑郁药物缓解
批准号：
410637
负责人：
Mueller Daniel J
金额：
$64.65万
依托单位：
Centre for Addiction and Mental Health (Toronto)
依托单位国家：
加拿大
项目类别：
Operating Grants
财政年份：
2019
资助国家：
加拿大
项目状态：
已结题
起止时间：
2019-09-01 至 2024-09-01
来源：
https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=410637&lang=en
关键词：
Antidepressants Genetics Late-Life Depression Machine Learning Pharmacogenetics Polygenic Risk Scores Predictive Modelling Treatment Response

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中文摘要
翻译
目前，仅在安大略，抑郁症的绝对医疗费用就相当于12亿美元。治疗首次发作重度抑郁症的老年人（年龄50岁或以上，影响高达16%的老年人），
英文摘要
The absolute health care cost of depression currently equals $1.2 billion in Ontario alone. Treating older adults with the first onset of major depressive disorder (age 50 years or older, affecting up to 16% of older adults) results in a 30-50% increase i
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Journal of Genetics and Genomics