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Explainable Artificial Intelligence and Process Mining Applications for Healthcare : Third International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings / edited by Jose M. Juarez, Carlos Fernandez-Llatas, Concha Bielza, Owen Johnson, Primoz Kocbek, Pedro Larrañaga, Niels Martin, Jorge Munoz-Gama, Gregor Štiglic, Marcos Sepulveda, Alfredo Vellido.

Springer Nature - Springer Computer Science eBooks 2024 English International Available online

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Format:
Book
Contributor:
Juarez, Jose M., editor.
Series:
Communications in Computer and Information Science, 1865-0937 ; 2020
Language:
English
Subjects (All):
Artificial intelligence.
Computer science.
Application software.
Computer science--Mathematics.
Data structures (Computer science).
Information theory.
Artificial Intelligence.
Theory of Computation.
Computer and Information Systems Applications.
Mathematics of Computing.
Data Structures and Information Theory.
Local Subjects:
Artificial Intelligence.
Theory of Computation.
Computer and Information Systems Applications.
Mathematics of Computing.
Data Structures and Information Theory.
Physical Description:
1 online resource (140 pages)
Edition:
1st ed. 2024.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Summary:
This book constitutes the proceedings of the Third International Workshop on Explainable Artificial Intelligence in Healthcare, XAI-Healthcare 2023, and the First International Workshop on Process Mining Applications for Healthcare, PM4H 2023, which took place in conjunction with AIME 2023 in Portoroz, Slovenia, on June 15, 2023. The 7 full papers included from XAI-Healthcare were carefully reviewed and selected from 11 submissions. They focus on all aspects of eXplainable Artificial Intelligence (XAI) in the medical and healthcare field. For PM4H 5 papers have been accepted from 17 submissions. They deal with data-driven process analysis techniques in healthcare. .
Contents:
International Workshop on Explainable Artificial Intelligence in Healthcare
Unlocking the Power of Explainability in Ranking Systems: A Visual Analytics Approach with XAI Techniques
Explainable Artificial Intelligence Solutions for Musculoskeletal Rehabilitation
An Explainable AI Framework for Treatment Failure Model for Oncology Patients
Feature selection in bipolar disorder episode classification using cost-constrained methods
ProbExplainer: A library for unified explainability of probabilistic models and an application in interneuron classification
Interpreting Machine Learning models for Survival Analysis: A study of Cutaneous Melanoma using the SEER Database
Explanations of Symbolic Reasoning to Effect Patient Persuasion and Education
International Workshop on Process Mining applications for Healthcare
PMApp: an Interactive Process Mining toolkit for building Healthcare Dashboards
A data-driven framework for improving clinical management of severe paralytic ileus in ICU: From path discovery, model generation to empirical validation
Phenotypes vs Processes: supporting the disease progression understanding in Type 2 Diabetes
From Script to Application. A bupaR-PMApp Bridge for Process Mining Research
Understanding Prostate Cancer care process using Process Mining: a Case Study. .
Notes:
Includes bibliographical references and index.
ISBN:
3-031-54303-3

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