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Data Management and Analysis Core

数据管理与分析核心

基本信息

批准号：
10698191
负责人：
SCOTT N COMPTON
金额：
$ 25.3万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-07 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10698191
关键词：
Adaptive Behaviors Address Advisory Committees Behavioral Biological Markers Caregivers Caring Child Clinical Trials Collaborations Communication Computer Vision Systems Computing Methodologies Consent Data Data Analyses Data Collection Data Reporting Data Set Data Storage and Retrieval Databases Dedications Detection Development Devices Diagnostic Doctor of Philosophy Early identification Electroencephalography Ensure Equipment Equity Faculty Family Goals Health Insurance Portability and Accountability Act Individual Knowledge Language Leadership Manuals Measurement Measures Methodology Methods Monitor Neurocognitive Outcome Outcome Measure Participant Patient Recruitments Patterns of Care Phase Phenotype Play Policies Preparation Procedures Process Productivity Protocols documentation Publications Quality Control Reporting Reproducibility of Results Research Research Methodology Research Personnel Role Science Scientist Screening procedure Secure Security Standardization Statistical Data Interpretation Structure Surveys Testing Training Work adult with autism spectrum disorder autism spectrum disorder autistic children behavioral outcome biomarker discovery brain based data acquisition data cleaning data integrity data management data quality data sharing data submission demographics design digital digital health experience file format improved individuals with autism spectrum disorder informatics infrastructure innovation novel outreach participant retention programs quality assurance recruit screening social communication timeline tool virtual

项目摘要

ABSTRACT – Data Management and Analysis Core The overall goal of the Duke Autism Center of Excellence (ACE) is to use a translational digital health and computational approach to address the critical need for more effective autism screening tools, objective outcome measures, and brain-based biomarkers that can be used in clinical trials with young autistic children. The Data Management and Analysis Core (DMAC) will support coordination of high-quality data collection, management, and analysis across the Duke ACE Projects and Cores. These Projects and Cores aim to apply shared, cutting- edge computational research methods to develop effective digital health tools for early autism detection and outcome monitoring and discover novel brain-based autism biomarkers. DMAC will play a key role in the Center’s ability to achieve its goals by overseeing consistent application of scientific standards and methodological rigor. DMAC will ensure clear, replicable acquisition protocols, post-processing analytic approaches, and data management and storage across a wide range of measurement domains, including electroencephalography, computer vision analytic measures, neurocognitive ability, language/social communication, adaptive behaviors, patterns of caregiver-child interaction, and diagnostic assessments. DMAC will employ well-justified data acquisition standards and innovative analytics within a secure informatics infrastructure designed to facilitate collaboration among the synergistic ACE Projects and Cores. The primary aims of DMAC are to (1) oversee the design and implementation of experimental protocols for acquisition of all study-related measures; (2) provide data acquisition and management support across all Projects and Cores; and (3) provide support and assistance with analyses of Center Projects, and in collaboration with investigators, conduct statistical analyses to address the specific aims of Projects and Cores. DMAC also will provide timely submissions of data to the National Database for Autism Research. This Core will also provide regular reports to the Center leadership, Executive Committee, External Advisory Committee, and individual investigators related to participant recruitment and retention, timelines, deliverables, protocol deviations, quality control indicators, scientific data, and outreach and dissemination activities. By providing these essential data management and analysis functions for all Projects and Cores, DMAC will ensure that the Duke ACE reaches its goals.

数据管理和分析核心