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Auteur
Dr. Sherry-Ann Brown is the Director of Cardio-Oncology at Froedtert Hospital & Milwaukee VA Medical Center and an Assistant Professor at the Medical College of Wisconsin, specializing in cardio-oncology and preventive cardiology, especially in women. In her role as Director of Cardio-Oncology, she has collaborated with colleagues to build the Cardio-Oncology program at MCW to facilitate innovative clinical and translational research linked to the Cardio-vascular Research Center and Cancer Center and have also encouraged physicians to increase clinical trials participation and cultivate investigator-initiated trials pertaining to cardio-oncology research. Dr. Brown is board-certified in cardiology and internal medicine. She has several years of clinical and academic experience where she has worked full-time in well reputed cancer institutions, such as The Mayo Clinic, Rochester, Minnesota. She is the author of more than 80 scientific articles in international high impact journals, book chapters, and comments on her area of specialty.
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Innovations in Cardio-Oncology: Artificial Intelligence, Digital Health, and Precision Medicine examines the benefits of big data analysis and future advancements in individualized medicine in cardio-oncology. The book helps readers understand and maximize the benefits of existing AI algorithms by integrating AI and digital health technologies into the clinical workflow, exploring AI orchestration, testing of AI applications, processing steps, active involvement and collaboration of qualified employees, and many other factors. The book introduces cardio-oncology and describes the prevention, screening and surveillance in cardio-oncology, followed by several chapters on the emerging role of the applications of mHealth, telemedicine and Artificial intelligence in cardio-oncology.
The book also highlights many societal and evidence-based recommended pathways for equitable digital health deployment and utilization in cardio-oncology care. It anticipates that exposing the potential for AI algorithms and innovative health tools widens the already existing healthcare disparities, including inequalities related to race, ethnicity, gender, socioeconomic level, lack of health insurance, linguistic and cultural barriers, systemic discrimination, and limited healthcare access.
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