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Artificial Intelligence and Data Mining in Healthcare de Malek Masmoudi

Artificial Intelligence and Data Mining in Healthcare

Editat de Malek Masmoudi, Bassem Jarboui, Patrick Siarry
en Limba Engleză Paperback – 26 ian 2022
This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection.
The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

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Paperback (1) 96309 lei  6-8 săpt.
  Springer International Publishing – 26 ian 2022 96309 lei  6-8 săpt.
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Specificații

ISBN-13: 9783030452421
ISBN-10: 3030452425
Ilustrații: XIX, 195 p. 62 illus., 39 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.31 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Cuprins

Artificial Intelligence for Healthcare Logistics: An Overview and Research Agenda.- Synergy Between Predictive Mining and Prescriptive Planning of Complex Patient Pathways Considering Process Discrepancies for Effective Hospital-Wide Decision Support.- Real-Time Capacity Management and Patient Flow Optimization in Hospitals Using AI Methods.- How Healthcare Expenditure Influences Life Expectancy: Case Study on Russian Regions.- Operating Theater Management System: Block-Scheduling.- An Immune Memory and a Negative Selection to Visualize Clinical Pathways from Electronic Health Records.- Optimized Medical Images Compression for Telemedicine Applications.- Online Variational Learning Using Finite Generalized Inverted Dirichlet Mixture Model with Feature Selection on Medical Data Sets.- Entropy-Based Variational Inference for Semi-bounded Data Clustering in Medical Applications.

Textul de pe ultima copertă

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection.
The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

Caracteristici

Presents recent work on healthcare management and engineering using AI and data mining techniques Valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics There is a growing need for intelligent decision-making techniques in healthcare