Dr. Rashidi combines his passion for patient care, research and education with his unique training in bioinformatics and machine learning (ML) to create innovative new tools (i.e. MILO, STNG, Pitt-GPT, etc.) and resources (Hematology Outlines, Cleveland Clinic’s AI course, etc.) that improve clinical practice, research and education. His experience in ML dates back to his graduate years at UCSD which subsequently allowed him to serve as the principal author and editor of several popular bioinformatics textbooks. This background has also enabled him to develop various novel AI-ML platforms. Before joining U Pitt / UPMC, he served as the founding director of Cleveland Clinic’s PLMI Center for AI and Data Science & Vice Chair of Technology Innovation & Computational Pathology, and before that he served as the Director of AI for University of California Davis Medical Center and Professor & Vice chair of informatics, leading a large number of AI studies with numerous collaborators from various prominent institutions. These experiences and studies have also led to numerous products (most recent of which bring the on-prem LLM framework Pitt-GPT) & several filed patents (e.g. the University of California IP MILO: Machine Intelligence Learning Optimizer, the proprietary Automated ML platform & it’s suite of 6 complimentary separate unique Data Science Apps & Cleveland Clinic’s new automated synthetic data generator and Validation platform STNG, Synthetic Tabular Neural Generator) along with a large number of manuscripts in which he serves as corresponding author. These products have been licensed to several industry and academic institutions & serving as a powerful suite of data science tools for a large number of clinical, quality and educational projects while also starting to help optimize and expedite data access needs for all investigators.
In addition to the above, Dr. Rashidi is also a well known educator with numerous teaching awards who has created some of the AppStore’s most popular hematology Apps along with Cleveland Clinic’s most recent AI-ML course (launched Cleveland Clinic wide in Jan 2024). He is also the co-founder and senior editor of HematologyOutlines, a very popular digital hematology atlas that is used internationally and endorsed by the American Society of Clinical Pathology. Dr. Rashidi’s efforts in the AI-ML & digital space are internationally recognized, as evidenced by his continuous invited talks at prominent conferences & institutions, his various journal AI/ML editorial & reviewer roles, his multitude of key invited review articles & his continued national committee roles within this space.
Learn more about his work:
– MILO for Education: https://milo-ml.com/milo-for-education/
– Supervised landscape ML overview, review article (2019): https://journals.sagepub.com/doi/full/10.1177/2374289519873088
– Statistics overview in Machine learning, review article (2023): https://www.frontiersin.org/articles/10.3389/fonc.2023.1130229/full
– Overview of ML Data types & preprocessing concepts along with a nice comprehensive glossary of ML terms (2023): https://www.sciencedirect.com/science/article/pii/S0740257023000138
– ML study design best practices along with current and future directions such as synthetic data usage, etc. (using coagulation/thrombosis study assessments as an example in this review article): 2022: https://www.jthjournal.org/article/S1538-7836(22)18293-0/fulltext
– Synthetic Data review Article (GPTs, GANs, Diffusion platforms, what is synthetic data & its utilities in medicine: https://www.sciencedirect.com/science/article/pii/S0023683724017732?via%3Dihub
