Atjaunināt sīkdatņu piekrišanu

Approaches and Applications of Deep Learning in Virtual Medical Care [Multiple-component retail product]

Edited by , Edited by , Edited by
  • Formāts: Multiple-component retail product, 293 pages, height x width: 279x216 mm, Contains 1 Hardback and 1 Digital (delivered electronically)
  • Sērija : Advances in Healthcare Information Systems and Administration
  • Izdošanas datums: 25-Feb-2022
  • Izdevniecība: Medical Information Science Reference
  • ISBN-10: 1668446774
  • ISBN-13: 9781668446775
Citas grāmatas par šo tēmu:
  • Multiple-component retail product
  • Cena: 509,88 €
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
Approaches and Applications of Deep Learning in Virtual Medical Care
  • Formāts: Multiple-component retail product, 293 pages, height x width: 279x216 mm, Contains 1 Hardback and 1 Digital (delivered electronically)
  • Sērija : Advances in Healthcare Information Systems and Administration
  • Izdošanas datums: 25-Feb-2022
  • Izdevniecība: Medical Information Science Reference
  • ISBN-10: 1668446774
  • ISBN-13: 9781668446775
Citas grāmatas par šo tēmu:
The recent advancements in the machine learning paradigm have various applications, specifically in the field of medical data analysis. Research has proven the high accuracy of deep learning algorithms, and they have become a standard choice for analyzing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Approaches and Applications of Deep Learning in Virtual Medical Care considers the applications of deep learning in virtual medical care and delves into complex deep learning algorithms, calibrates models, and improves the predictions of the trained model on medical imaging. Covering topics such as big data and medical sensors, this critical reference source is ideal for researchers, academicians, practitioners, industry professionals, hospital workers, scholars, instructors, and students.
Dr. Noor Zaman received a Ph.D. degree in IT from UTP, Malaysia. He has great international exposure in academia, research, administration, and academic quality accreditation. He was with ILMA University, KFU for a decade, and is currently with Taylors University, Malaysia. He has 19 years of teaching and administrative experience. Besides scientific research activities, he had worked a decade for academic accreditation and earned ABET accreditation twice for three programs at CCSIT, King Faisal University, Saudi Arabia. Dr. Noor Zaman has recently been awarded as a top reviewer (1% globally) by WoS/ISI (Publons). He has edited/authored more than 11 research books with international and reputed publishers, earned several research grants, and has a great number of indexed research articles on his credit. He has supervised several postgraduate students including masters and Ph.D candidates. He is an Associate Editor of IEEE ACCESS, Guest editor of several reputed journals, member of the editorial board of several research journals, and an active TPC member of reputed conferences around the globe.