Artificial intelligence and data mining in healthcare : / edited by Malek Masmoudi, Bassem Jarboui, Patrick Siarry
Contributor(s): Masmoudi, Malek, editor literario | Jarboui, Bassem, editor literario | Siarry, Patrick, editor literario | SpringerLink
Material type:
E-bookPublisher: Cham, Switzerland : Springer International Publising, 2021Edition: First edition 2021.Description: 1 recurso en línea (XIX, 195 páginas) : 62 ilustraciones, 39 ilustraciones a color.ISBN: 9783030452407.Subject: Inteligencia artificial en medicina
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | R859.7 .A78 2021 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.26042250 |
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.
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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