LEADER 03919nam 22006015 450 001 9910872197303321 005 20240708125243.0 010 $a9789819737055$b(electronic bk.) 010 $z9789819737048 024 7 $a10.1007/978-981-97-3705-5 035 $a(MiAaPQ)EBC31520449 035 $a(Au-PeEL)EBL31520449 035 $a(CKB)32691729200041 035 $a(DE-He213)978-981-97-3705-5 035 $a(OCoLC)1445769490 035 $a(EXLCZ)9932691729200041 100 $a20240708d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExplainable AI in Health Informatics /$fedited by Rajanikanth Aluvalu, Mayuri Mehta, Patrick Siarry 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (287 pages) 225 1 $aComputational Intelligence Methods and Applications,$x2510-1773 311 08$aPrint version: Aluvalu, Rajanikanth Explainable AI in Health Informatics Singapore : Springer,c2024 9789819737048 327 $aChapter 1. Introduction to Explainable AI -- Chapter 2. Explainable AI Methods and Applications -- Chapter 3. Unveil the Black Box Model for Healthcare Explainable AI -- Chapter 4. Explainable AI: Methods, Frameworks, and Tools for Healthcare 5.0 -- Chapter 5. Explainable AI in Disease Diagnosis -- Chapter 6. Explainable Artificial Intelligence in Drug Discovery -- Chapter 7. Explainable AI for Big Data Control -- Chapter 8. Patient Data Analytics using XAI- Existing Tools & Case Studies -- Chapter 9. Enhancing Diagnosis of Kidney Ailments from CT Scan with Explainable AI -- Chapter 10. Explainable AI for Colorectal Cancer Classification -- Chapter 11. Explainable AI (XAI)-based Robot-Assisted Surgical classification Procedure -- Chapter 12. Explainable AI Case Studies in Healthcare. 330 $aThis book provides a comprehensive review of the latest research in the area of explainable artificial intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases. 410 0$aComputational Intelligence Methods and Applications,$x2510-1773 606 $aArtificial intelligence 606 $aMedical informatics 606 $aBiomedical engineering 606 $aArtificial Intelligence 606 $aHealth Informatics 606 $aMedical and Health Technologies 615 0$aArtificial intelligence. 615 0$aMedical informatics. 615 0$aBiomedical engineering. 615 14$aArtificial Intelligence. 615 24$aHealth Informatics. 615 24$aMedical and Health Technologies. 676 $a006.3 700 $aAluvalu$b Rajanikanth$01744221 701 $aMehta$b Mayuri$01737946 701 $aSiarry$b Patrick$0860327 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910872197303321 996 $aExplainable AI in Health Informatics$94174047 997 $aUNINA