Artificial Intelligence (AI) has the potential to transform entirely the medical profession, from patient education and physician training to clinical practice and advanced research. AI also has limitations and can interfere with the physician-patient relationship and data privacy. There is a need to critically review the ethical aspects of AI to avoid deleterious results. This book will be centered on how AI can help to deliver better outcomes.

Claudio Tinoco Mesquita is an Associate Professor at the Faculty of Medicine, Fluminense Federal University. Editor-in-chief of the International Journal of Cardiovascular Sciences. Graduated in Medicine from the Fluminense Federal University (1994), Master’s in Medicine (Cardiology) from the Federal University of Rio de Janeiro (1999) and Ph.D. in Medicine and Nuclear Medicine from the Federal University of Rio de Janeiro (2002). Has experience in Medicine, focusing on Cardiology, acting on the following subjects: myocardial scintigraphy, cardiology, nuclear medicine, heart failure and nuclear medicine. Research collaborator at the Università Degli Studio di Brescia in Italy, visiting professor at Spedalli Civilli di Brescia (2018) and with an active research line in collaboration with the radiology and nuclear medicine department. CNPq Productivity Scholarship. Scientist of the State of Rio de Janeiro by FAPERJ.

Aline Paes is an Associate Professor in the Institute of Computing at the Fluminense Federal University (UFF). “Young Scientist of Our State” by FAPERJ. CNPq Productivity Scholarship. Leader of the research group MeLLL-UFF (Machine Learning and Language Learning), a virtual lab at UFF. D.Sc. and an M.Sc. degree in Systems Engineering and Computer Science (PESC/COPPE, UFRJ). Visiting scholar at Imperial College London, UK, in 2008. Interests and contributions in the following topics: relational machine learning, integrated with neural, statistical and logical techniques, natural language processing, updating and adapting models with transfer learning, explainable AI, and AI for social good. Regularly publishes in one of the leading journals of the ML (Machine Learning Journal), among others, and in national and international AI conferences. Editorial board member of Machine Learning Journal and Inteligencia Artificial, an IBERAMIA journal.

Davi Shunji Yahiro is an MD-PhD student in Cardiovascular Sciences at the Universidade Federal Fluminense (UFF), supported by a CAPES scholarship. He is a member of the Cardiovascular Imaging Research Group at UFF, with academic interests centered on Internal Medicine, Cardiology, Nuclear Medicine, and Cardiovascular Imaging. His research focuses on health technology assessment and the application of artificial intelligence, machine learning, and natural language processing in medical imaging, particularly myocardial perfusion imaging, PET-CT, cardiac amyloidosis, and coronary artery disease diagnosis. He has experience in systematic reviews, meta-analyses, health economics, and cost-effectiveness analyses of advanced imaging modalities.