# SCH: Transfer Regression to Enable Cross-Domain Cardiovascular Event Prediction

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2024 · $299,604

## Abstract

SCH: Transfer Regression to Enable Cross-Domain Cardiovascular Event Prediction
This project proposes fundamental novelties (e.g., transfer volume regression) in computer science, data
science, and biomedical engineering to address the critical health challenge of lacking a standardized
clinical risk prediction for major cardiovascular events (CVe)—defined as stroke, heart attack, heart failure
(HF), and death. Our proposal includes a pioneering transfer regression learning method, combined with
several novel machine learning and data science techniques, to develop the first smart, standardized,
fairness-aware, and user-friendly CVe prediction model. This model leverages commonly used, low-cost
(sometimes free), safe, and quick screening programs (featuring low radiation and no need for contrast
agents), aiming to significantly enhance clinical outcomes. The efficacy and robustness of this model are
to be validated using four large and diverse datasets, exemplifying a significant advancement in Smart
Health and Biomedical Research in the era of Artificial Intelligence and Advanced Data Science (SCH).
RELEVANCE (See instructions):
 We will develop and validate transfer volume regression to enable quantitative clinical risk predictions for
 major cardiovascular events (defined as stroke, heart attack, heart failure, and death in this proposal) to
 guide preventive therapy.

## Key facts

- **NIH application ID:** 11062600
- **Project number:** 1R01HL177813-01
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** SHUO LI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $299,604
- **Award type:** 1
- **Project period:** 2024-09-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11062600

## Citation

> US National Institutes of Health, RePORTER application 11062600, SCH: Transfer Regression to Enable Cross-Domain Cardiovascular Event Prediction (1R01HL177813-01). Retrieved via AI Analytics 2026-06-25 from https://api.ai-analytics.org/grant/nih/11062600. Licensed CC0.

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