# Building and implementing a TBI prognostic model featuring real-time analysis of brain CT images

> **NIH NIH R01** · DUKE UNIVERSITY · 2022 · $662,301

## Abstract

Scope of Work
Duke will complete all work for the machine learning model building and implementation of the model into the
Duke clinical workflow. For Aim 1 of the project, this work will include data extraction and cleaning, neural network
architecture design, and model optimization and validation. For Aim 2, this work will include establishment of
technical infrastructure for real-time image and access and processing, construction of a front-end dashboard in
close collaboration with frontline clinicians, and deployment and prospective validation of the model. The latter
step will also consist of education and training of hospital users. For Aim 3 of the project, Duke will guide staff at
Jefferson through the model implementation and validation process, with the active integration and training
performed by staff at Jefferson. In Aim 3 Duke will also run the experiments on multi-site model generalization,
using retrospective data at both Duke and Jefferson. Data will be shared between Duke and Jefferson via secure
ethernet transfer between Jefferson’s secure data warehouse and Duke’s Protected Analytics and Computing
Environment. The end goal of the work will be to provide a sophisticated, high-accuracy, and seamlessly
integrated tool for predicting the risk of actionable TBI complications over the course of a TBI patient’s hospital
encounter. This method, which will augment decision-making for treating a complex neurological condition, will
significantly improve overall TBI outcomes, reduce readmission rates, and minimize the extraordinary costs
incurred by inefficient provision of healthcare resources.

## Key facts

- **NIH application ID:** 10446746
- **Project number:** 1R01NS123275-01A1
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Timothy William Dunn
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $662,301
- **Award type:** 1
- **Project period:** 2022-06-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10446746

## Citation

> US National Institutes of Health, RePORTER application 10446746, Building and implementing a TBI prognostic model featuring real-time analysis of brain CT images (1R01NS123275-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10446746. Licensed CC0.

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