Nicholas J. Primiano, M.S. M.D., is a physician, researcher, software developer, and biomedical engineer with a penchant for quantitative, cross-disciplinary inquiry. Recently, he has applied his expertise to developing an AI model that automatically measures the distance between the carina and the endotracheal tube on chest X-rays, showcasing the practical applications of artificial intelligence in improving medical diagnostics.

Other recent academic contributions include a paper in the Journal of Digital Imaging detailing an AI technique for measuring the Insall-Salvati ratio, an important parameter in orthopedic imaging. Prior to this, Nicholas was engaged in work on generative AI to create synthetic data, a important endeavor in enhancing the diversity and volume of datasets available for training more robust AI models in medical imaging.

Currently, a research track radiology resident at Mount Sinai West in New York City, Nicholas is immersed in developing a multi-modal vision-language model for the detection of pathology in chest radiographs. This work represents a step forward in the utilization of AI for more nuanced and comprehensive medical image interpretation.

Nicholas’s educational background is as diverse as his professional endeavors. He holds degrees from Columbia University, where his senior thesis contributed to the development of a laser alignment aid for ultrasound-guided biopsies, and from Fordham University, where he delved into computer science and applied mathematics, leading to innovative projects like software for multi-robot navigation. In addition, Nicholas holds an M.S. in Bioethics from Columbia University, complementing his robust background in biomedical engineering and technology.

His works have been featured in various scientific publications, reflecting a career committed to the advancement of medical technology through meticulous research and development.