Détail de l'auteur
Auteur Boris GALITSKY |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Faire une suggestion Affiner la recherche
Artificial Intelligence for Healthcare Applications and Management / Boris GALITSKY / ELSEVIER SCIENCE (2022)
Titre : Artificial Intelligence for Healthcare Applications and Management Type de document : e-book Auteurs : Boris GALITSKY Editeur : ELSEVIER SCIENCE Année de publication : 2022 ISBN/ISSN/EAN : 9780128245217 Note générale : copyrighted Langues : Anglais (eng) Résumé : Artificial Intelligence for Healthcare Applications and Management introduces application domains of various AI algorithms across healthcare management. Instead of discussing AI first and then exploring its applications in healthcare afterward, the authors attack the problems in context directly, in order to accelerate the path of an interested reader toward building industrial-strength healthcare applications. Readers will be introduced to a wide spectrum of AI applications supporting all stages of patient flow in a healthcare facility. The authors explain how AI supports patients throughout a healthcare facility, including diagnosis and treatment recommendations needed to get patients from the point of admission to the point of discharge while maintaining quality, patient safety, and patient/provider satisfaction. AI methods are expected to decrease the burden on physicians, improve the quality of patient care, and decrease overall treatment costs. Current conditions affected by COVID-19 pose new challenges for healthcare management and learning how to apply AI will be important for a broad spectrum of students and mature professionals working in medical informatics. This book focuses on predictive analytics, health text processing, data aggregation, management of patients, and other fields which have all turned out to be bottlenecks for the efficient management of coronavirus patients. Presents an in-depth exploration of how AI algorithms embedded in scheduling, prediction, automated support, personalization, and diagnostics can improve the efficiency of patient treatment Investigates explainable AI, including explainable decision support and machine learning, from limited data to back-up clinical decisions, and data analysis Offers hands-on skills to computer science and medical informatics students to aid them in designing intelligent systems for healthcare Informs a broad, multidisciplinary audience about a multitude of applications of machine learning and linguistics across various healthcare fields Introduces medical discourse analysis for a high-level representation of health texts Nombre d'accès : Illimité En ligne : https://neoma-bs.idm.oclc.org/login?url=https://www.scholarvox.com/book/88930558 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=550507
LIBRARY - Campus Rouen
NEOMA Business School
pmb
-
59 Rue Taittinger, 51100 Reims
-
00 33 (0)3 26 77 46 15
Library Campus Reims
-
1 Rue du Maréchal Juin, BP 215
76825 Mont Saint Aignan cedex -
00 33 (0)2 32 82 58 26