LEADER 03717nam 2200529 450 001 9910484050503321 005 20230522162957.0 010 $a981-16-0811-3 024 7 $a10.1007/978-981-16-0811-7 035 $a(CKB)4100000011918712 035 $a(DE-He213)978-981-16-0811-7 035 $a(MiAaPQ)EBC6607150 035 $a(Au-PeEL)EBL6607150 035 $a(OCoLC)1250304658 035 $a(PPN)255887590 035 $a(EXLCZ)994100000011918712 100 $a20220118d2021 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial intelligence and machine learning in healthcare /$fAnkur Saxena, Shivani Chandra 205 $a1st ed. 2021. 210 1$aGateway East, Singapore :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (XIX, 228 p. 119 illus., 88 illus. in color.) 311 $a981-16-0810-5 327 $aChapter 1_Big Data Analytics and AI for Healthcare -- Chapter 2_Genetics with Big Data and AI -- Chapter 3_AI and Big Data for next-generation sequencing -- Chapter 4_Artificial Intelligence for Computational Biology -- Chapter 5_Artificial intelligence and machine learning in clinical development -- Chapter 6_Big data analytics for personalized medicine -- Chapter 7_Generating and Managing Healthcare data with AI -- Chapter 8_Big Data and Artificial Intelligence for diseases -- Chapter 9_Artificial Intelligence and Big Data for Public Health -- Chapter 10_Biasness in Healthcare Big Data and Computational Algorithms -- Chapter 11_AI and ML in Healthcare: An Ethical perspective. 330 $aThis book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare. 606 $aArtificial intelligence$xMedical applications 606 $aIntel·ligència artificial en medicina$2thub 606 $aAprenentatge automàtic$2thub 608 $aLlibres electrònics$2thub 615 0$aArtificial intelligence$xMedical applications. 615 7$aIntel·ligència artificial en medicina 615 7$aAprenentatge automàtic 676 $a610.285 700 $aSaxena$b Ankur$01074806 702 $aChandra$b Shivani 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484050503321 996 $aArtificial intelligence and machine learning in healthcare$92581921 997 $aUNINA LEADER 05592nam 22006974a 450 001 996211220303316 005 20230617004805.0 010 $a1-280-74324-7 010 $a9786610743247 010 $a0-470-79556-5 010 $a0-470-75914-3 010 $a1-4051-7315-7 035 $a(CKB)1000000000342144 035 $a(EBL)284177 035 $a(OCoLC)85810080 035 $a(SSID)ssj0000226863 035 $a(PQKBManifestationID)11184531 035 $a(PQKBTitleCode)TC0000226863 035 $a(PQKBWorkID)10259408 035 $a(PQKB)10255895 035 $a(MiAaPQ)EBC284177 035 $a(EXLCZ)991000000000342144 100 $a20040330d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPreviously developed land$b[electronic resource] $eindustrial activities and contamination /$fPaul Syms 205 $a2nd ed. 210 $aOxford, UK ;$aMalden, MA $cBlackwell$dc2004 215 $a1 online resource (256 p.) 300 $aEnl. ed. of: Desk reference guide to potentially contaminative land uses. 311 $a1-4051-0697-2 320 $aIncludes bibliographical references (p. 225-230) and index. 327 $aContents; Foreword; Preface; Biographies; Part A Issues Influencing Redevelopment and Value; 1 Introduction and policy context; 1.1 Introduction; 1.2 Overview of government policy on sustainable development and previously developed land (PDL); 1.3 Development agencies; 1.4 Other organisations; 1.5 Environmental Protection Act 1990, Part IIA; 1.6 Contaminated Land Exposure Assessment (CLEA); 1.7 Summary; Checklist; 2 Approaches to valuation; 2.1 Introduction; 2.2 Recent and current research; 2.3 Valuation of 'non-investment' properties; 2.4 Stigma and the effects of 'time' and 'information' 327 $a2.5 SummaryChecklist; 3 Barriers to redevelopment; 3.1 Introduction; 3.2 Fear of the unknown; 3.3 Regulatory controls; 3.4 Delays and increased costs; 3.5 Stigma; 3.6 Overcoming the barriers; Checklist; 4 Recording land condition; 4.1 Introduction; 4.2 Information on land condition; 4.3 The Land Condition Record (LCR); 4.4 The Specialist in Land Condition (SiLC) Registration scheme; 4.5 Conclusions; Checklist; 5 A few legal predictions; 5.1 Introduction; 5.2 Relevant laws; 5.3 Economic and fiscal instruments; 5.4 Energy and climate change; 5.5 Corporate governance and financial reporting 327 $a5.6 ConclusionChecklist; 6 Modernising the British planning system; 6.1 Introduction; 6.2 The component elements of the British planning system; 6.3 The passage of time; 6.4 The Government's case for modernising the British planning system; 6.5 The Government's system - change proposals; 6.6 Changing the culture of planning; 6.7 The challenge of change; Checklist; 7 Geographical Information Systems; 7.1 Introduction; 7.2 GIS and previously developed land; 7.3 Using a GIS database to assist in the redevelopment of PDL; 7.4 Other historical datasets and maps; 7.5 Current sources; 7.6 Conclusion 327 $aChecklistPart B Industrial Activities and Contamination; 8 Industrial activities and their potential to cause contamination; 8.1 Introduction; 8.2 The potential for contamination; 8.3 The Land Use Categories - a brief description; 8.4 Summary; Industrial Activities: contaminants, processes and case studies; Airports and similar uses; Animal slaughtering and by-products; Asbestos manufacture and use; Concrete, ceramics, cement and plaster works; Disinfectants manufacture; Dockyards and wharves; Electrical and electronics manufacture, including semi-conductor manufacturing plants 327 $aElectricity generatingEngineering; Explosives industry, including fireworks manufacture; Fertiliser manufacture; Film and photographic processing; Fine chemicals, including dyestuffs and pigments manufacturing; Food processing, including brewing and malting, distilling of spirits; Garages, including sale of automotive fuel, repair of cars and bikes; Gasworks, coke works, coal carbonisation and similar; Glass manufacture; Iron and steelworks; Laundries and dry-cleaning; Metal smelting and refining, including furnaces and forges, electroplating, galvanising and anodising 327 $aMining and extractive industries 330 $aThe redevelopment of former industrial sites, so-called 'brownfield' sites, is becoming increasingly important as space is required for inner city commercial developments and as housebuilders are forced by government policy to recycle land rather than using 'greenfield' sites. This guide, originally issued in 1999 by the Incorporated Society of Valuers and Auctioneers under the title reference Desk Reference Guide to Potentially Contaminative Land Uses identifies those industrial land uses most likely to be encountered by valuers and developers, gives guidance on the type of contaminati 606 $aBrownfields$zGreat Britain 606 $aBrownfields$xLaw and legislation$zGreat Britain 606 $aReclamation of land$zGreat Britain 606 $aSoil pollution$xRisk assessment$zGreat Britain 615 0$aBrownfields 615 0$aBrownfields$xLaw and legislation 615 0$aReclamation of land 615 0$aSoil pollution$xRisk assessment 676 $a333.77 676 $a690 700 $aSyms$b Paul M$0855354 701 $aSyms$b Paul M$0855354 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996211220303316 996 $aPreviously developed land$91909558 997 $aUNISA