Center for Suicide Research and Prevention - Methods Core

自杀研究和预防中心 - 方法核心

• 批准号: 10575950
• 负责人: Andrea S Foulkes
• 金额: $ 143.79万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-08 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10575950
• 关键词: Algorithms; Bioinformatics; Biometry; Calibration; Clinical Informatics; Clinical Trials; Collaborations; Communities; Complex; Computer software; Data; Data Collection; Data Science; Development; Electronic Health Record; Engineering; Ensure; Evaluation; Funding; General Hospitals; Goals; Healthcare Systems; Heart; Hour; Informatics; Internet; Intervention; Investigation; Lead; Leadership; Learning; Manuscripts; Massachusetts; Medicine; Methodology; Methods; Monitor; Multi-Institutional Clinical Trial; National Institute of Mental Health; Observational Study; Online Systems; Phase; Pilot Projects; Play; Population; Positioning Attribute; Post-Acute Sequelae of SARS-CoV-2 Infection; Predictive Analytics; Preparation; Prevention; Procedures; Public Health Schools; Quality Control; Recording of previous events; Recurrence; Reporting; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Resources; Risk Estimate; Role; Safety; Sample Size; Site; Statistical Data Interpretation; Suicide; Suicide prevention; Training; Translations; United States Department of Veterans Affairs; United States National Institutes of Health; Validation; Work; Writing; algorithm training; biomedical informatics; causal model; clinical decision support; clinical development; clinical predictors; data management; data quality; data resource; design; experience; feature selection; fitbit; high dimensionality; implementation strategy; improved; innovation; machine learning method; medical schools; meetings; member; novel; prediction algorithm; professor; research study; risk prediction; sound; statistical and machine learning; statistics; suicidal risk; supervised learning; transfer learning; treatment effect; wearable device; wearable monitor; web site

The Methods Core (MC) will facilitate efficient and robust transdisciplinary research for the proposed Center for Suicide Prevention and Research (CSRP) through apposite application and evaluation of leading-edge statistical approaches for integrative predictive analysis of complex real-world and clinical trial data. The overriding goal of the MC is to support application and evaluation of sound statistical principles and approaches to enhance and enable novel implementation strategies for improved suicide prevention efforts. The MC team includes a distinguished team of biostatisticians and informaticians with expertise in clinical trials, statistical and machine learning methods for high-dimensional real-world data, and a clinical informatics team with expertise in development and implementation of Applications to be incorporated at the bedside. The team members have an extensive history of collaboration with investigators constituting the proposed CSRP and are extremely well-positioned to deliver (i) data collection, data synthesis and app development; (ii) support the development and conduct of CSRP research studies; (iii) develop and validate novel clinical prediction algorithms; and (iv) dissemination to the research community.

方法核心(MC)将促进拟议的中心的高效和强大的跨学科研究 自杀预防与研究(CSRP)通过对前沿的恰当应用和评估 复杂的真实世界和临床试验数据的综合预测分析的统计方法。这个 MC的首要目标是支持应用和评估合理的统计原则和 加强和启用新的实施战略的方法，以改进自杀预防工作。 MC团队包括一支由具有临床专业知识的生物统计学家和信息学家组成的杰出团队 高维真实世界数据的试验、统计和机器学习方法，以及临床信息学 在开发和实施应用程序方面具有专业知识的团队将在床边合并。这个 团队成员与构成拟议的CSRP的调查人员有着广泛的合作历史 并处于极其有利的地位，能够提供(I)数据收集、数据合成和应用程序开发；(Ii) 支持CSRP研究的开发和实施；(3)开发和验证新的临床研究 预测算法；以及(4)向研究界传播。