AI is transforming translational research by accelerating the journey from bench to bedside. By integrating vast datasets from genomics, imaging, clinical trials, and electronic health records, Perelman School of Medicine researchers are working to discover ways in which AI enables faster identification of biomarkers, predictive modeling of disease progression, and personalized treatment strategies. Through Machine learning algorithms, investigators are uncovering hidden patterns that inform drug discovery and optimize clinical decision-making. As our research continues to evolve, its role in bridging the gap between laboratory findings and real-world medical applications is becoming indispensable—paving the way for more precise, efficient, and patient-centered healthcare solutions.
