Artificial Intelligence in Urologic Malignancies

Auteur
Dr. Arora is Assistant Professor in Department of Urology at Sylvester Cancer Centre, University of Miami. He is the recipient of the Young Investigator Award from Regional Center for Biotechnology, UNESCO, for working on drug discovery in cancer. In 2016 he joined the University of Miami as a research scientist. He has several peer reviewed articles, patents, and grants. In 2019 he was promoted to a faculty position at the University of Miami. Currently, his lab is focusing on exploring therapeutic efficacy of Nitric oxide donors against different stages of Prostate cancer progression, using Nitric oxide donors in combination with currently available immune checkpoint inhibitors, and using machine learning tools to study the progression of prostate cancer and applying this knowledge in building up translational tools that could be used by researchers, clinicians and patients.

Texte du rabat

Artificial Intelligence in Urologic Malignancies describes current artificial intelligence technology, with an emphasis on prostate cancer applications. The book provides guidance on how artificial intelligence can improve therapeutics, how the power of artificial intelligence integrated with current standard therapy and research can enhance decision-making, and proposes future directions on how to integrate artificial intelligence within clinical applications. This is the perfect reference for scientists and researchers interested in the basic translational research opportunities such as drug discovery, pharmacogenetics, and experimental therapeutics, as well as clinicians interested in how AI applications are integrated with applications.

Contenu

1. Current Advancements of ML in Healthcare 2. Machine Learning and Pathology: A Historical Perspective 3. AI in Personalized Medicine: Application of Genomics to Influence Therapy Decisions 4. AI in Personalized Medicine: Using public repositories to understand patterns in relevant datasets 5. Mutational Landscape of Cancer and how Latest Technologies can help in simplifying the understanding 6. ChatGPT and Healthcare- current and future prospects 7. Adversarial Networks - Enhancing current methodology with new models 8. Limitations of AI in Healthcare