Importance of Data Quality in AI Model Design: Cedars-Sinai Insights

LOS ANGELES (July 11, 2024) -- Dr. David Ouyang, a leading cardiologist at Cedars-Sinai's Smidt Heart Institute, emphasizes the crucial role of data quality in optimizing artificial intelligence (AI) systems.

Dr. Ouyang, also a faculty member in Cedars-Sinai's Division of Artificial Intelligence, has conducted extensive research into AI applications for cardiovascular disease analysis. His recent studies offer valuable insights into the nuanced development of these systems.

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One of his studies, featured in JACC: Advances, examines how case selection influences the accuracy of AI models. Focused on detecting cardiac amyloidosis, a condition marked by abnormal protein accumulation in heart tissues, the research underscores the impact of varied disease definitions on model performance.

"In light of cardiac amyloidosis being underdiagnosed, AI models trained on datasets of high-risk patients can significantly aid clinicians in early detection," Dr. Ouyang explained.

Dr. Lily Stern, a fellow investigator at Cedars-Sinai, collaborated on the JACC: Advances study.

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In another significant contribution, published in NEJM AI, Dr. Ouyang and colleagues leverage electrocardiogram (ECG) data to train deep-learning AI models for heart failure detection. The study contrasts AI models trained on clinical measurements, such as ejection fraction, with those relying solely on diagnostic records. It demonstrates the superior precision achieved with detailed numerical data.

"This study highlights the advantage of training AI models with precise clinical measurements over descriptive diagnoses," noted Amey Vrudhula, a fellow researcher at Cedars-Sinai and lead author of the study.

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"We've accumulated invaluable insights into AI model design through extensive healthcare AI training," Dr. Ouyang emphasized, highlighting their potential impact on future research initiatives.

Dr. Neal Yuan, also from Cedars-Sinai, contributed to the study's findings.

News Source:- newswise.com