Methods Core

方法核心

• 批准号: 10475475
• 负责人: PATRICK J HEAGERTY
• 金额: $ 29.9万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-21 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10475475
• 关键词: Adopted; Algorithms; Area; Artificial Intelligence; Automobile Driving; Biomedical Research; Biometry; Characteristics; Clinical; Clinical Data; Clinical Informatics; Clinical Research; Clinical Services; Clinical Trials; Code; Cohort Studies; Collaborations; Collection; Communities; Data; Data Collection; Data Coordinating Center; Data Science; Development; Diagnosis; Diagnostic; Disease; Electronic Health Record; Fostering; Foundations; Funding; Goals; Health Services Research; Health Technology; Heterogeneity; Informatics; Information Retrieval; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10); Lead; Leadership; Learning; Machine Learning; Measurement; Medical Imaging; Methodology; Methods; Mission; Modernization; Monitor; Musculoskeletal; Musculoskeletal Diseases; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Natural Language Processing; Observational Study; Outcome; Patient Outcomes Assessments; Patients; Phase; Phenotype; Positioning Attribute; Prevention; Procedures; Process; Radiology Specialty; Randomized; Randomized Clinical Trials; Reporting; Reproducibility; Research; Research Design; Research Methodology; Role; Secure; System; Telephone; Text; United States National Institutes of Health; Universities; Use Effectiveness; Validation; Washington; algorithm development; clinical center; clinical development; cluster trial; comparative effectiveness; convolutional neural network; data quality; data science infrastructure; design; electronic structure; flexibility; health care delivery; high dimensionality; image processing; innovation; learning algorithm; mHealth; machine learning method; novel; pragmatic trial; quality assurance; randomized trial; research data dissemination; statistical and machine learning; statistics; treatment effect; trial design; unstructured data

The goal of the Methodologic Core is to support high-impact clinical research focusing on the diagnosis, treatment, and prevention of musculoskeletal diseases. Specifically, the Methodologic Core will provide the contemporary data science infrastructure necessary for studies that leverage electronic health records (EHR), and for trials that collect patient reported outcomes. We will organize around two major themes encompassing multiple activities: confirmatory learning which includes design and analysis of observational studies and randomized trials; and predictive learning which leverages contemporary machine learning and artificial intelligence for processing electronic health records data and other high-dimensional information. The data sciences are driving innovation in clinical research with the linkage of multiple EMR systems opening new opportunities for large-scale clinical learning. Ultimately rigorous research demands new methods for the extraction of reliable information and requires the design of trials that can tailor to the unique characteristics of patients and the context of health care delivery systems. The University of Washington Center for Biomedical Statistics (CBS) has provided informatics and statistical leadership to multiple observational and randomized studies focusing on musculoskeletal disorders and is uniquely positioned to provide the foundation for expanded impact within the broad scope of the NIAMS mission.

方法学核心的目标是支持高影响力的临床研究，重点关注