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Artificial Intelligence and Data Mining in Healthcare [electronic resource] /

Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2021Edition: 1st ed. 2021Description: XIX, 195 p. 62 illus., 39 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030452407
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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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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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