معرفی
Andrew Loza, MD, PhD, is an Instructor of Biomedical Informatics and Data Science at Yale School of Medicine. He holds joint appointments in both the Department of Biomedical Informatics and Data Science and the Department of Pediatrics. Dr. Loza is also affiliated with the VA Connecticut Healthcare System where he completed his Clinical Informatics fellowship and postdoctoral training.
Dr. Loza's educational background includes a PhD in Biophysics from Washington University in St. Louis (2016), where he studied mechanisms of collective cell migration using time lapse microscopy, computer vision, and simulation. He earned his MD from Yale University School of Medicine and completed his residency in Internal Medicine-Pediatrics at Yale. His training was further enhanced by a Clinical Informatics fellowship in the ACGME Yale/VA program and a postdoctoral fellowship in the VA Biomedical Informatics program.
Dr. Loza's research focuses on developing statistical and deep learning methods to leverage Real-World Data to improve clinical care, with particular emphasis on multimodal medical foundation models. His work spans several key areas including predictive analytics for patient risk assessment, analysis of electronic health record patterns, and understanding the impact of healthcare interventions. The Loza Lab aims to transform data into actionable information that can be seamlessly integrated into clinical workflows to enhance patient care without disrupting physician workflow.
His research demonstrates strong trends in applying advanced computational methods to solve healthcare delivery challenges, particularly in pediatric care, population health management, and clinical decision support. Dr. Loza's work bridges the gap between complex data science techniques and practical clinical applications, with a focus on creating tools that physicians can readily use in their daily practice.
- Hartwell Foundation Award 2024 for Pediatric Predictive Modeling
Dr. Loza is actively involved in mentoring and has expressed interest in developing the next generation of physician-scientists who can bridge clinical medicine and data science. His work at the intersection of Yale and the VA Connecticut Healthcare System provides unique opportunities to develop and test predictive models across different healthcare settings. Current projects include developing transformer-based generative models for healthcare applications and refining data collection processes to better inform clinical decision-making.
The Loza Lab operates at the forefront of biomedical informatics, leveraging the resources of both Yale School of Medicine and the VA Connecticut Healthcare System to develop innovative solutions for healthcare delivery challenges. The lab's work emphasizes practical implementation of predictive models that can be integrated into clinical workflows without disrupting physician-patient interactions.
