Improving heart attack diagnosis using artificial intelligence
Using Predictive Modeling for Acute Coronary Syndrome Screening to Improve Timely Diagnosis and Mortality for STEMI
This study is working on using artificial intelligence to help emergency departments quickly and accurately identify heart attacks, especially for women and people of color who might not get diagnosed as fast, so everyone can receive the care they need within the first 10 minutes of arriving.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-10999429 on NIH RePORTER |
What this research studies
This research focuses on enhancing the identification of ST-elevation myocardial infarction (STEMI) through the use of artificial intelligence (AI) in emergency departments. It aims to ensure that all patients, particularly women and non-white individuals who often face diagnostic delays, receive timely ECGs within a critical 10-minute window upon arrival. By developing an AI model that addresses these biases, the project seeks to improve the accuracy and speed of diagnosis, ultimately leading to better patient outcomes. The methodology involves analyzing clinical data and implementing AI-driven decision support tools to streamline the screening process.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals presenting with symptoms of acute coronary syndrome, particularly women and non-white patients who are at higher risk of diagnostic delays.
Not a fit: Patients who do not exhibit symptoms of acute coronary syndrome or those who are not seeking emergency care may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly reduce mortality rates from heart attacks by ensuring faster and more accurate diagnoses for all patients.
How similar studies have performed: Previous research has shown that AI-based approaches can improve diagnostic accuracy and reduce treatment delays in various medical conditions, indicating a promising potential for success in this area.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: Yiadom, Maame Yaa A.b. — Stanford University
- Study coordinator: Yiadom, Maame Yaa A.b.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.