Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications - Couverture souple

Couverture souple

ISBN 10 : 0443136718 ISBN 13 : 9780443136719

Editeur : Academic Press Inc, 2024

Synopsis

Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field.

This book will be beneficial for academics, professionals in the IT industry, educators, students, and anyone else involved in the use and development of AI in the medical field.

• Covers the basic concepts of Artificial Intelligence and Machine Learning, methods and practices, and advanced topics and applications to clinical and precision medicine
• Presents readers with an understanding of how AI is revolutionizing medicine by demonstrating the applications of computational intelligence to the field, along with an awareness of how AI can improve upon traditional medical structures
• Provides researchers, practitioners, and project stakeholders with a complete guide for applying AI techniques in their projects and solutions

A propos du livre

À propos des auteurs

Dr. Shai Ben-David earned his PhD in mathematics from the Hebrew University. Over the years, he has been a Professor at the Technion, Haifa, Israel and held visiting faculty positions at the Australian National University, Cornell University, ETH Zurich, and TTI Chicago. His research interests span a
range of topics including logic, theory of distributed computation, machine learning, and complexity theory. He routinely serves as a senior area chair in the major machine learning conferences (NeurIPS, ICML, AISTATS, COLT and ALT) and won best paper awards in COLT 2006, NeurIPS 2018 and ALT 2023. He is a co-author of a popular textbook "Understanding Machine Learning: From theory to practice."

Dr. Giuseppe Curigliano, MD PhD, is a Full Professor of Medical Oncology at the University of Milan and the Chief of the Clinical Division of Early Drug Development at European Institute of Oncology, Milan, Italy. Dr. Curigliano is an expert in the field of advanced drug development in solid tumors, with specific interest in breast cancer. He contributed to the development of many anticancer treatments currently available as standard of care in the treatment of multiple solid tumors. Dr Curigliano in 2022 was identified as Clarivate(TM) world's most influential researchers. Dr Curigliano has contributed to over 670 peer-reviewed publications.

Dr. David Koff, Professor Emeritus and past Chair of the Department of Radiology is the founder and director of MIIRCAM, the Medical Imaging Informatics Research Centre at McMaster University, where he oversees research initiatives on electronic transmission and workflow integration of medical images and AI applications in medical imaging. He co-developed the Canadian standards for lossy compression. He is a member of the IHE section of the RSNA's Medical Informatics committee and a co-founder of IHE Canada (Integrating the Healthcare Enterprise).

Détails de l'édition

• Éditeur: Academic Press Inc
• Date d'édition: 2024
• ISBN 10: 0443136718
• ISBN 13: 9780443136719
• Reliure: Broché
• Langue: anglais
• Nombre de pages: 294
• Éditeur: David PhD Shai Ben-, Curigliano MD PhD Giuseppe, Koff MD David, Jereczek-Fossa MD PhD Barbara Alicja, Torre PhD HDR Davide La, Pravettoni Gabriella
• Coordonnées du fabricant: non disponible