Sponsor Deadline
Posted: 3/14/2024

Notice of Special Interest (NOSI): Computational and Statistical Methods to Enhance Discovery from Health Data

The National Library of Medicine is issuing this Notice to highlight its interest in receiving grant applications focused on research that aims to reduce or mitigate gaps and errors in health data sets.

NLM invites research grant applications that propose innovative state-of-the-art methods and generalizable approaches to address problems with large health data sets or analytic tools, whether the data are obtained from electronic health records, public health data sets, biomedical imaging, omics repositories, literature, and social media data, or other biomedical or social/behavioral data sets. Applications in response to this NOSI are expected to help address AI ethical issues and mitigate algorithm bias caused by data problems.

Areas of interest include but are not limited to (1) developing and testing innovative, generalizable and scalable computational or statistical approaches, including ones for a cloud computing environment, applied to large and/or merged health data sets holding human or non-human data, with a focus on understanding and characterizing the gaps, errors, biases, and other limitations in the data or inferences based on the data; (2) exploring approaches to correct biases or compensate for missing data, including but not limited to the introduction of debiasing techniques, novel imputing methods, effective data sample strategies, and policies or the use of synthetic data; (3) testing new statistical algorithms or other computational approaches to strengthen research designs for use with specific types of biomedical, biological, and social/behavioral data; (4) generating metadata that adequately characterizes the data, including its provenance, intended use, and processes by which it was collected and verified; (5) improving approaches for integrating, mining, and analyzing health data from multiple sites, sources, cohorts and research domains that preserve the confidentiality, accuracy, completeness and overall security of the data. Applicants should address ethical issues that might arise from their proposed approach.

This notice applies to due dates on or after February 5, 2023 and subsequent receipt dates through January 8, 2026.

 

NOT-LM-23-001