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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 de Jose M. Juarez

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: Communications in Computer and Information Science, cartea 2020

Editat de 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
en Limba Engleză Paperback – 26 feb 2024
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. 
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Specificații

ISBN-13: 9783031543029
ISBN-10: 3031543025
Pagini: 131
Ilustrații: XII, 131 p. 59 illus., 47 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.21 kg
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

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.