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245 1 0 _aExplainable Artificial Intelligence and Process Mining Applications for Healthcare
_h[electronic resource] :
_bThird International Workshop, XAI-Healthcare 2023, and First International Workshop, PM4H 2023, Portoroz, Slovenia, June 15, 2023, Proceedings /
_cedited 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.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXII, 131 p. 59 illus., 47 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aCommunications in Computer and Information Science,
_x1865-0937 ;
_v2020
505 0 _aInternational 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. .
520 _aThis 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. .
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer science.
_99832
650 0 _aApplication software.
_998247
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aData structures (Computer science).
_98188
650 0 _aInformation theory.
_914256
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aTheory of Computation.
_998251
650 2 4 _aComputer and Information Systems Applications.
_998252
650 2 4 _aMathematics of Computing.
_931875
650 2 4 _aData Structures and Information Theory.
_931923
700 1 _aJuarez, Jose M.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_998255
700 1 _aFernandez-Llatas, Carlos.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_998256
700 1 _aBielza, Concha.
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_998257
700 1 _aJohnson, Owen.
_eeditor.
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_998259
700 1 _aKocbek, Primoz.
_eeditor.
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_998260
700 1 _aLarrañaga, Pedro.
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_998261
700 1 _aMartin, Niels.
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700 1 _aMunoz-Gama, Jorge.
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_4http://id.loc.gov/vocabulary/relators/edt
_998264
700 1 _aŠtiglic, Gregor.
_eeditor.
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700 1 _aSepulveda, Marcos.
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700 1 _aVellido, Alfredo.
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710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031543029
776 0 8 _iPrinted edition:
_z9783031543043
830 0 _aCommunications in Computer and Information Science,
_x1865-0937 ;
_v2020
_998273
856 4 0 _uhttps://doi.org/10.1007/978-3-031-54303-6
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