David G. Bostwick, MD, MBA, FCAP

David G. Bostwick, MD, MBA, FCAP

Dr. David G. Bostwick, MD, MBA, FCAP, is the founder and Chief Executive Officer of Bostwick Laboratories (a division of Poplar Healthcare), Chief Medical Officer of Granger Genetics, and Chief Medical Officer of Rampart Health. He trained at the University of Maryland and Stanford University, and was formerly a Professor of Urology and Pathology at the Mayo Clinic from 1991 to 1999. Dr. Bostwick is internationally renowned, with 40 years of experience and interest in prostate cancer, bladder cancer and urologic diseases. He has previously held appointments at the National Cancer Institute, Stanford University, University of Chicago, University of Maryland, and Mayo Clinic. 

Dr. Bostwick has authored 17 books, more than 25 book chapters, and more than 475 professional papers. Dr. Bostwick has presented more than 2000 lectures around the world, and has served as Principal Investigator or Co-Investigator for more than 10 clinical trials.

Talks by David G. Bostwick, MD, MBA, FCAP

Role of Digital Pathology and AI in Improving Diagnostic Accuracy

David G. Bostwick, MD, MBA, FCAP, explores the role of artificial intelligence (AI) and digital pathology in advancing diagnostic accuracy in prostate cancer. In this 19-minute presentation, Dr. Bostwick addresses the limitations of using biopsies and radical prostatectomies as the gold standard in prostate cancer diagnosis. Despite its high initial costs and operational challenges, he emphasizes that digital pathology holds transformative potential for standardization and efficiency in pathology practices.

Dr. Bostwick delves into the long-standing application of AI in pathology, highlighting its ability to reduce human workloads. Advances in digital pathology have improved resolution, speed, and data transfer capabilities, enabling better integration of AI tools for detecting and grading cancer.

Dr. Bostwick asserts the future of pathology lies in 3D optical slicing and deep learning algorithms, which allow for precise tumor quantification and three-dimensional reconstructions of tissues. These methods could revolutionize grading systems, offering unparalleled accuracy and data granularity.

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