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DESCRIPTION (provided by applicant): The long-term objective of this research is to develop new information technology that will significantly reduce barriers to interdisciplinary and cross-facility biomedical research collaboration. This Fast-Track proposal will result in commercial software that will allow mental health and neuroimaging investigators to (1) effectively design and execute custom experiment protocols and workflow, (2) more easily acquire and manage multimedia research data from heterogeneous clinical systems, and (3) selectively share data with remote interdisciplinary collaborators. The resulting software, to be called BioSCRIBE, will consist of a flexible, extensible toolkit for constructing web-based experiment management systems that are custom-tailored to the unique workflow and data models of the investigator's own image-based research project. The tool-kit will provide a visual interface for architecting a structural model of the researcher's unique experiment processes and metadata. This model will be used to automatically generate a clinical information system that is tailored to manage the acquisition, analysis, and sharing of the research group's multimodal experiment data. Software development will be driven by formative design evaluation, in collaboration with neuroimaging and mental health researchers at interdisciplinary centers at the University of Washington and Harvard Medical School who will use the toolkit to support longitudinal research in autism, bipolar disorder, and other disorders. Preliminary results demonstrate that custom experiment management systems are highly useful to clinical researchers. However, these systems are hard to build with current tools, requiring an expensive development effort, and specialized software developer expertise. The BioSCRIBE toolkit will greatly reduce the effort required to build a custom experiment management system, allowing researchers to benefit from advances in biomedical content management and collaborative knowledge sharing technologies. BioSCRIBE will enable investigators to securely and selectively control access to data and files at a fine granularity, and deploy workflow management solutions that will lead to increased productivity, reduced errors, and improved process repeatability. As such, it will have strong commercial potential as a software product aimed at hospitals, universities, and private research labs.
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Acuity - A Clinical Decision Support System for Applied Behavior Analysis
  • 批准号:
    10552494
  • 项目类别:
  • 资助金额:
    $68.0万
  • 财政年份:
    2022
  • 负责人:
    REX M JAKOBOVITS
  • 依托单位:
Acuity - A Clinical Decision Support System for Applied Behavior Analysis
  • 批准号:
    10681393
  • 项目类别:
  • 资助金额:
    $68.73万
  • 财政年份:
    2022
  • 负责人:
    REX M JAKOBOVITS
  • 依托单位:
Goalspace: A Platform for Parent-Assisted Behavioral Interventions
  • 批准号:
    10674912
  • 项目类别:
  • 资助金额:
    $84.01万
  • 财政年份:
    2020
  • 负责人:
    REX M JAKOBOVITS
  • 依托单位:
Goalspace: A Platform for Parent-Assisted Behavioral Interventions
  • 批准号:
    10082395
  • 项目类别:
  • 资助金额:
    $54.93万
  • 财政年份:
    2020
  • 负责人:
    REX M JAKOBOVITS
  • 依托单位:
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