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NOBEL PRIZE 2026

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NIHEUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT

Data Science and Analytics for Precision Rehabilitation (DAPR) Center

Active
Institution
UNIVERSITY OF SOUTHERN CALIFORNIA, CA
Principal investigator
Sook-Lei Liew
Funding
$1.4M
Duration
2025–2030
Open portfolio

Moonbase score

Still being scored

Abstract

It is essential to have the proper administrative infrastructure in place so that the Data Science and Analytics for Precision Rehabilitation (DAPR) Center can effectively carry out its mission to improve the rigor of medical rehabilitation research and the efficacy of clinical rehabilitation treatment. To that end, the overall goal of the DAPR Administrative Core is to provide coordinated administrative and organizational support to DAPR’s faculty, researchers, collaborators, and community. The Administrative Core has three specific aims. Aim 1 is to manage the disparate set of DAPR personnel, institutions, and initiatives in a coherent manner. To support DAPR in developing resources and promoting effective community utilization, the Administrative Core will foster intricate coordination between the DAPR Leadership Team across Cores and all key personnel and provide strong fiscal management. The Administrative Core will ensure effective collaboration between DAPR and the national and international rehabilitation communities as well as with other Medical Rehabilitation Research Centers (MRCCs). Aim 2 is to continually self-monitor, evaluate, and verify that the Center remains on track to meet the aims of each Core and Project. The Administrative Core will implement a structured meeting schedule with clear metrics, following the CDC Approach to Program Evaluation, to monitor progress and make necessary adjustments. We will facilitate communication within DAPR and maintain close contact with NICHD, the External Advisory Committee, and the Community Advisory Committee to ensure alignment with critical goals. Progress will be reviewed bi-annually, focusing on positive changes in user community behavior regarding DAPR resource adoption and support. Aim 3 is to create and administer a pilot grant program that extends DAPR’s infrastructure into new rehabilitation-specific datatypes and conditions while providing learning opportunities for early career rehabilitation researchers. Category 1 pilot grants will support researchers in annotating and publicly sharing datasets using the DAPR schema, with hands-on support for data annotation and archive identification. Category 2 pilot grants will assist researchers in applying precision rehabilitation algorithms to their data, with support for data querying and algorithm application. This two-pronged pilot program aims to maximize NIH’s research investments by enhancing the management, sharing, and utilization of rehabilitation research data for precision rehabilitation. The achievement of these aims will lead to an efficient and effective DAPR Center that promotes the use of data science, large AI/ML-ready datasets, and advanced algorithms for personalized, precision rehabilitation. A successful DAPR Center will advance a culture of open science and data science across medical rehabilitation research, focusing on improving research efficiency, reducing research waste, and meeting the needs of PWLE through data-driven approaches.

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EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENTP50Special Emphasis Panel[ZHD1 DSR-N (55)]categoryrehabilitationprecisiondata scienceadvisory committeerehabilitation researchsupport datapilot grants

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