Giovanni Cacciamani, MD

Associate Professor of Research Urology

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Overview

Dr Giovanni Cacciamani is a urologist and surgeon-scientist, recognized internationally for his contributions to oncological diseases, patient safety, and the integration of artificial intelligence (AI) into healthcare. He is an Associate Professor of Urology and Radiology Research at the University of Southern California (USC), USA and serves as the Director of the Artificial Intelligence Center for Surgical and Clinical Applications in Urology with cutting-edge research initiatives at the intersection of urology, technology, and clinical innovation.

Dr Cacciamani is also actively involved in shaping the future of AI and digital health in urology on a global scale. He chairs the Young Academic Urologists (YAU) UroTechnology and Digital Healthcare Group of the European Association of Urology (EAU), a role through which he promotes technological advancements and digital transformation in the field of Urology. He serves as Associate Editor for the Journal of Urology, for the section on Innovation and AI.

His dedication to healthcare innovation has been widely recognized. In 2022, he was honored as Citizen of the Year (Italy) for his pioneering work in medical technology, and he received the Italian Matula Award, the most prestigious recognition for the best Italian urologist under 40.

Dr Cacciamani has authored about 400 scientific publications (H-Index 43 – Scopus 05/2026) and has delivered over 250 lectures worldwide on emerging technologies, AI, and digital medicine applications in urology. His lab at USC is currently exploring the potential of Generative AI (GAI) in healthcare, focusing on making AI more accessible and practical for practicing physicians. With a deep commitment to bridging technology and clinical practice, Dr Cacciamani goal is conducting innovative research and education efforts, shaping the future of AI-driven urology and digital healthcare worldwide.

Publications

  • CHA Studies: What are They, How are They Evolving in Healthcare, and How Do We Respond? J Clin Epidemiol. 2026 Jul 18; 112424. Huo B, Collins GS, Cacciamani GE , Yu A, Guyatt G . View in PubMed
  • GUSL: A novel and efficient machine learning model for prostate segmentation on MRI. Comput Biol Med. 2026 Aug 15; 213:111820.. View in PubMed
  • Improving readability of layperson abstracts and summaries in oncology using task-specific large language model powered tool: results from the BRIDGE-AI 7 study. JAMIA Open. 2026 Jun; 9(3):ooag082.. View in PubMed
  • Enhancing the quality and trustworthiness of large language model-generated summaries of clinical oncology literature. JAMIA Open. 2026 Jun; 9(3):ooag078.. View in PubMed
  • Intermediate clinical endpoints as surrogates for overall survival after salvage prostatectomy. BJU Int. 2026 Jun 15.. View in PubMed
  • Readability of sexual health educational materials: a comparative analysis of ISSM resources and large language model-generated content. J Sex Med. 2026 Jun 05; 23(7).. View in PubMed
  • Development and validation of PEYRO-Q: a novel multidimensional patient-reported outcome measure for Peyronie’s disease. Sex Med. 2026 Aug; 14(4):qfag034.. View in PubMed
  • From data to decision: integrating causality AI and predictive analytics in endourological practice-a descriptive guide for clinicians from EAU Endourology. World J Urol. 2026 Mar 01; 44(1).. View in PubMed
  • A transparent, lightweight and sustainable Green Learning AI model for prostate cancer detection on MRI. BJU Int. 2026 Jun; 137(6):1014-1025.. View in PubMed
  • Leveraging generative AI to enhance doctor-patient communication. Nat Rev Urol. 2026 Feb 05.. View in PubMed