Hooman H. Rashidi
MD, MS FCAP
Dr.Rashidi is the Vice Chair of Technology Innovation & Computational Pathology, PLMI Director of PLMI’s Center for AI & Data Science Cleveland Clinic. Dr. Rashidi combines his passion for patient care and education with his unique training in machine learning (ML) to create innovative new tools and resources that improve clinical practice, research and education. He is a physician scientist, a prolific author & inventor and a well known educator with numerous teaching awards. His efforts in the AI-ML & digital space are internationally recognized, as evidenced by his numerous invited talks (at prestigious conferences / institutions), his various editorial & reviewer roles, the multitude of key invited review articles & his continued national committee roles within this space.
Rama Gullapalli, MD, PhD is a physician-scientist in the departments of Pathology, Chemical and Biological Engineering at the University of New Mexico (UNM). Dr. Gullapalli obtained his medical degree from the Armed Forces Medical College (AFMC) in India. He subsequently obtained a master’s degree in Electrical Engineering and a PhD in Bioengineering at The Pennsylvania State University. Dr. Gullapalli completed his residency in Clinical Pathology and a fellowship in Molecular Pathology at the University of Pittsburgh Medical Center (UPMC). On the clinical side, Dr. Gullapalli is interested in the convergence of technology with traditional pathology practice, with a focus on next generation sequencing, digital pathology, clinical informatics and personalized medicine. The Gullapalli research lab is currently focused on two key areas of research: 1) Cancers of the liver and gallbladder with a focus on environment-microbiome-inflammation interactions 2) Understanding the role of environmental heavy metals (e.g., Cadmium) as a risk factor of hepatobiliary pathophysiology. The Gullapalli lab brings to bear a wide variety of research methods such as high throughput sequencing, fluorescence optical techniques, bioinformatics, molecular biology and systems biology to understand the pathogenesis of hepatobiliary cancers.
– “The New Era of Synthetic Data, Auto-MLs and Generative Al integration in Medicine”: Hooman H. Rashidi MD, MS FCAP
– “AI in Pathology: Ethical Considerations and Current Topics”: Rama Gullapalli MD, PhD
- Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts
- Common statistical concepts in the supervised Machine Learning arena
- Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions
- Ethics of AI in Pathology: Current Paradigms and Emerging Issues