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001443338 019__ $$a1288633349$$a1288665130$$a1288964063$$a1289245080$$a1289368919$$a1295442159
001443338 020__ $$a9781484277805$$q(electronic bk.)
001443338 020__ $$a1484277805$$q(electronic bk.)
001443338 020__ $$z9781484277799
001443338 020__ $$z1484277791
001443338 0247_ $$a10.1007/978-1-4842-7780-5$$2doi
001443338 0248_ $$a9781484277799
001443338 0248_ $$a9781484277805
001443338 035__ $$aSP(OCoLC)1290489952
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001443338 049__ $$aISEA
001443338 050_4 $$aR859.7.A78
001443338 08204 $$a610.285/63$$223
001443338 1001_ $$aSuri, Abhinav,$$eauthor.
001443338 24510 $$aPractical AI for healthcare professionals :$$bmachine learning with Numpy, Scikit-learn, and TensorFlow /$$cAbhinav Suri.
001443338 250__ $$a1st edition.
001443338 264_1 $$a[United States] :$$bApress,$$c2022.
001443338 300__ $$a1 online resource (266 pages)
001443338 336__ $$atext$$btxt$$2rdacontent
001443338 337__ $$acomputer$$bc$$2rdamedia
001443338 338__ $$aonline resource$$bcr$$2rdacarrier
001443338 347__ $$atext file
001443338 365__ $$b34.99
001443338 500__ $$aIncludes index.
001443338 5050_ $$aChapter 1: Introduction to AI and its Use Cases- Chapter 2: Computational Thinking -- Chapter 3: Overview of Programming -- Chapter 4: A Brief Tour of Machine Learning Algorithms. -Chapter 5: Project #1 Neural Networks & Heart Disease -- Chapter 6: Project #2 CNNs & Brain Tumor Detection -- Chapter 7: The Future of Healthcare and AI.
001443338 506__ $$aAccess limited to authorized users.
001443338 520__ $$aUse Artificial Intelligence (AI) to analyze and diagnose what previously could only be handled by trained medical professionals. This book gives an introduction to practical AI, focusing on real-life medical problems, how to solve them with actual code, and how to evaluate the efficacy of these solutions. You'll start by learning how to diagnose problems as ones that can and cannot be solved with AI or computer science algorithms. If you're not familiar with those algorithms, that's not a problem. You'll learn the basics of algorithms and neural networks and when each should be applied. Then you'll tackle the essential parts of basic Python programming relevant to data processing and making AI programs. The TensorFlow library alogn with Numpy and Scikit-Learn are covered, too. Once you've mastered those basic computer science concepts, you can dive into three projects with code, implementation details and explanation, and diagnostic utility analysis. These projects give you the change to explore using machine learning algorithms for diagnosing diabetes from patient data, using basic neural networks for heart disease prediction from cardiac data, and using convolutional networks for brain tumor segmentation from MRI scans The topics and projects covered not only encompass areas of the medical field where AI is already playing a major role but also are engineered to cover as much as possible of AI that is relevant to medical diagnostics. Along the way, readers can expect to learn data processing, how to conceptualize problems that can be solved by AI, and how to program solutions to problems using modern libraries, such as TensorFlow. Physicians and other healthcare professionals who can master these skills will be able to lead AI-based research and diagnostic tool development, ultimately benefiting countless patients. What You'll Learn Distinguish between problems that currently can and cannot be solved with AI Master programming concepts not familiar to physicians, such as libraries, coding, and creating and training ML models Perform dataset analysis with decision trees, SVMs, and neural networks. Who This Book Is For Physicians and other healthcare professionals  curious about AI and interested in leading medical innovation initiatives. Additionally, software engineers working on healthcare related projects involving AI.
001443338 542__ $$f© Copyright 2022 Abhinav Suri.$$g2022
001443338 550__ $$aMade available through: Safari, an O'Reilly Media Company.
001443338 588__ $$aOnline resource; Title from title page (viewed December 13, 2021).
001443338 650_0 $$aArtificial intelligence$$xMedical applications.
001443338 650_0 $$aMachine learning.
001443338 650_6 $$aIntelligence artificielle en médecine.
001443338 650_6 $$aApprentissage automatique.
001443338 655_0 $$aElectronic books.
001443338 7102_ $$aO'Reilly for Higher Education (Firm),$$edistributor.
001443338 7102_ $$aSafari, an O'Reilly Media Company.
001443338 77608 $$iPrint version:$$aSuri, Abhinav$$tPractical AI for Healthcare Professionals$$dBerkeley, CA : Apress L. P.,c2021$$z9781484277799
001443338 852__ $$bebk
001443338 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-1-4842-7780-5$$zOnline Access$$91397441.1
001443338 909CO $$ooai:library.usi.edu:1443338$$pGLOBAL_SET
001443338 980__ $$aBIB
001443338 980__ $$aEBOOK
001443338 982__ $$aEbook
001443338 983__ $$aOnline
001443338 994__ $$a92$$bISE