Using AI to Detect ECG Abnormalities

The growing use of artificial intelligence (AI) for medical applications is creating new tools for physicians to provide better patient care and improve health outcomes. Two recent student-led research projects have uncovered potential new uses of AI modeling techniques for heart health, increasing the efficiency and accuracy of cardiac diagnoses.

In a collaboration between the College of Osteopathic Medicine (NYITCOM) and the College of Engineering and Computing Sciences’ Entrepreneurship and Technology Innovation Center (ETIC), students and faculty worked on complementary research projects to detect electrocardiogram (ECG) abnormalities using AI models. The two groups approached the research from different angles—one from a clinical perspective and the other from a computer engineering perspective.

Thanks to the College of Engineering and Computing Sciences’ collaborative agreement with Catholic Health on Long Island, the two research teams obtained a robust set of anonymized ECG data. The two individual New York Tech research teams worked together to clean and normalize the data to create a reliable dataset of ECG results that they could use for analysis, prediction, and decision-making. The two teams then used the dataset to train and test multiple AI models to identify the algorithms that produced the most accurate and consistent predictions.

“The AI model could produce output that establishes results as abnormal, and then a doctor can go back and look at the result again if the AI model is showing something different than what they’re interpreting as medical professionals,” says Michael Nizich, Ph.D., director of the ETIC. “We’ll always need the professionally trained doctor, and this model can give the medical professional one more tool to use through the results stemming from these students’ efforts.”