Innovations in Cardio-Oncology: Artificial Intelligence, Digital Health, and Precision Medicine reviews the benefits of biomedical technologies and advancements in individualized medicine, with applications in cardio-oncology.
Illustrations of work involving machine learning and natural language processing help readers understand and maximize the benefits of artificial intelligence (AI) algorithms, with integration of AI and digital health technologies into the clinical workflow for personalized patient care, research, and provider and patient education.
In 31 chapters, Innovations in Cardio-Oncology: Artificial Intelligence, Digital Health, and Precision Medicine introduces the emergent medical field at the interface of cardiology and oncology, cardio-oncology, and describes prevention, screening and surveillance, followed by several chapters on the role of the applications of digital health, telemedicine, and AI in cardio-oncology precision care. The book also highlights many medical society guidelines and evidence-based recommended pathways for equitable digital health deployment and utilization in cardio-oncology care. This book anticipates that AI algorithms and innovative health tools have the potential to address, and does not have to widen, the already existing healthcare disparities, including inequalities related to race, ethnicity, gender, socioeconomic level, health insurance status, linguistic and cultural barriers, systemic discrimination, and healthcare access.
This book provides valuable practical guidance for healthcare professionals, scientists, learners, and patients to integrate digital health platforms into their clinical practice, research, and patient engagement models, fit for individual use and also for multi-stakeholder groups from academia, technology, and industry, with shared interests in applying Innovation (Digital Health, mHealth, Telemedicine, Telehealth, Informatics, Precision Health, Computational Medicine, Social Media, Artificial Intelligence including Machine Learning, Deep Learning, Natural Language Processing, and Neural Networks, & more) to Cardiology and Oncology clinical practice, research, and education.
