- Titulinis
- Dalykinė ir mokslinė literatūra
- Humanitarinių mokslų knygos
- Artificial Intelligence for Healthcare Applications and Management
Saveli Goldberg
Artificial Intelligence for Healthcare Applications and Management
Balsavo 0
ISBN: 9780128245217
Autorius : Saveli Goldberg
Leidimo metai: 2022
Leidėjas: Academic Press
Leidinio kalba: Anglų
Formatas: Minkšti viršeliai
Formatas: 9×6
Autorius : Saveli Goldberg
Leidimo metai: 2022
Leidėjas: Academic Press
Leidinio kalba: Anglų
Formatas: Minkšti viršeliai
Formatas: 9×6
Kaina:
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Likutis pakankamas
Pristatymo terminas Lietuvoje 3-6 savaitės
Pristatymo terminas Lietuvoje 1-4 darbo dienos
Pristatymo terminas Lietuvoje 3-6 savaitės
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Aprašymas
<p><i><b>Artificial Intelligence for Healthcare Applications and Management</b> </i>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.</p> <p>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.</p>
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