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001440750 001__ 1440750
001440750 003__ OCoLC
001440750 005__ 20230309004659.0
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001440750 019__ $$a1282596442$$a1283140314$$a1283855764$$a1287777262$$a1292518531
001440750 020__ $$a9783030764098$$q(electronic bk.)
001440750 020__ $$a3030764095$$q(electronic bk.)
001440750 020__ $$z9783030764081
001440750 020__ $$z3030764087
001440750 0247_ $$a10.1007/978-3-030-76409-8$$2doi
001440750 035__ $$aSP(OCoLC)1282006037
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001440750 049__ $$aISEA
001440750 050_4 $$aQ335$$b.E96 2021
001440750 08204 $$a006.3$$223
001440750 24500 $$aExplainable AI within the digital transformation and cyber physical systems :$$bXAI methods and applications /$$cMoamar Sayed-Mouchaweh, editor.
001440750 264_1 $$aCham :$$bSpringer,$$c[2021]
001440750 264_4 $$c©2021
001440750 300__ $$a1 online resource :$$billustrations
001440750 336__ $$atext$$btxt$$2rdacontent
001440750 337__ $$acomputer$$bc$$2rdamedia
001440750 338__ $$aonline resource$$bcr$$2rdacarrier
001440750 347__ $$atext file
001440750 347__ $$bPDF
001440750 500__ $$aIncludes index.
001440750 5050_ $$aIntroduction -- Part 1 Methods used to generate explainable models -- Explainable Artificial Intelligence (XAI) -- intrinsic explainable models -- model-agnostic methods -- Part 2 Evaluation layout and meaningful criteria -- expressive power -- portability evaluation layout -- accuracy evaluation layout -- algorithmic complexity -- fidelity evaluation -- stability evaluation -- representativeness evaluation layout -- local/global explanation -- Part 3 XAI applications within the context of digital transformation and cyber-physical systems -- applications of XAI in decision support tools -- smart energy management -- finance -- telemedicine and healthcare -- critical systems -- e-government -- Conclusion.
001440750 506__ $$aAccess limited to authorized users.
001440750 520__ $$aThis book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
001440750 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 16, 2021).
001440750 650_0 $$aArtificial intelligence.
001440750 650_6 $$aIntelligence artificielle.
001440750 655_0 $$aElectronic books.
001440750 7001_ $$aSayed-Mouchaweh, Moamar,$$eeditor.
001440750 77608 $$iPrint version:$$z3030764087$$z9783030764081$$w(OCoLC)1246351412
001440750 852__ $$bebk
001440750 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-76409-8$$zOnline Access$$91397441.1
001440750 909CO $$ooai:library.usi.edu:1440750$$pGLOBAL_SET
001440750 980__ $$aBIB
001440750 980__ $$aEBOOK
001440750 982__ $$aEbook
001440750 983__ $$aOnline
001440750 994__ $$a92$$bISE