9789819642403 - machine learning for disease detection, prediction and diagnosis: challenges and opportunities di choudhury, tanupriya; katal, avita (12 risultati)
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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Da: Majestic Books, Hounslow, , Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore Jun 2025 2025
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Da: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, , GermaniaRheinberg-Buch Andreas Meier eK
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Buch. Condizione: Neu. Neuware -The book Machine Learning for Disease Detection, Prediction, and Diagnosis can be a comprehensive guide to the novel concepts, techniques, and frameworks essential for improving the viability of existing machine-learning practices. It provides an in-depth analysis of how these new technologies are… helpful to detect, predict and diagnose diseases more accurately. The book covers various topics such as image classification algorithms, supervised learning methods like support vector machines (SVM), deep neural networks (DNNs), convolutional neural networks (CNNs), etc. unsupervised approaches such as clustering algorithms as well as reinforcement learning strategies.This book is an invaluable resource for anyone interested in machine-learning applications related to disease detection or diagnosis. It explains different concepts and provides practical examples of how they can it implements using real-world data sets from medical imaging datasets or public health records databases, among others. Furthermore, it offers insights into recent advances made by researchers which have enabled automated decision-making systems based on AI models with improved accuracy over traditional methods. This text also discusses ways through which current models could improve further by incorporating domain knowledge during the model training phase, thereby increasing their efficacy even further.Overall, this book serves as a great source of information about the latest advancements made in the field of Machine Learning & Artificial Intelligence towards efficient building systems capable enough detecting & diagnosing diseases automatically while avoiding human errors resulting due manual intervention at any stage along process pipeline thus ensuring better outcomes overall. Moreover, it helps readers understand the underlying principles behind each technique discussed so that they may apply them according to their own application scenarios efficiently without worrying much about the implementation details required to get the job done the right way the first time around itself! 404 pp. Englisch.
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Da: moluna, Greven, , Germaniamoluna
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Da: preigu, Osnabrück, Germaniapreigu
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Buch. Condizione: Neu. Machine Learning for Disease Detection, Prediction, and Diagnosis | Challenges and Opportunities | Tanupriya Choudhury (u. a.) | Buch | xviii | Englisch | 2025 | Springer | EAN 9789819642403 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann…[at]springer[dot]com | Anbieter: preigu.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 153,90
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Buch. Condizione: Neu. Neuware - The book Machine Learning for Disease Detection, Prediction, and Diagnosis can be a comprehensive guide to the novel concepts, techniques, and frameworks essential for improving the viability of existing machine-learning practices. It provides an in-depth analysis of how these new technologies ar…e helpful to detect, predict and diagnose diseases more accurately. The book covers various topics such as image classification algorithms, supervised learning methods like support vector machines (SVM), deep neural networks (DNNs), convolutional neural networks (CNNs), etc. unsupervised approaches such as clustering algorithms as well as reinforcement learning strategies.This book is an invaluable resource for anyone interested in machine-learning applications related to disease detection or diagnosis. It explains different concepts and provides practical examples of how they can it implements using real-world data sets from medical imaging datasets or public health records databases, among others. Furthermore, it offers insights into recent advances made by researchers which have enabled automated decision-making systems based on AI models with improved accuracy over traditional methods. This text also discusses ways through which current models could improve further by incorporating domain knowledge during the model training phase, thereby increasing their efficacy even further.Overall, this book serves as a great source of information about the latest advancements made in the field of Machine Learning & Artificial Intelligence towards efficient building systems capable enough detecting & diagnosing diseases automatically while avoiding human errors resulting due manual intervention at any stage along process pipeline thus ensuring better outcomes overall. Moreover, it helps readers understand the underlying principles behind each technique discussed so that they may apply them according to their own application scenarios efficiently without worrying much about the implementation details required to get the job done the right way the first time around itself.
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- Edizione Internazionale
Da: UK BOOKS STORE, London, LONDO, Regno UnitoUK BOOKS STORE
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Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if t…he Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 118,26
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore Jun 2025 2025
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 149,79
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book Machine Learning for Disease Detection, Prediction, and Diagnosis can be a comprehensive guide to the novel concepts, techniques, and frameworks essential for improving the viability of existing machine-learning practices. It pro…vides an in-depth analysis of how these new technologies are helpful to detect, predict and diagnose diseases more accurately. The book covers various topics such as image classification algorithms, supervised learning methods like support vector machines (SVM), deep neural networks (DNNs), convolutional neural networks (CNNs), etc. unsupervised approaches such as clustering algorithms as well as reinforcement learning strategies.This book is an invaluable resource for anyone interested in machine-learning applications related to disease detection or diagnosis. It explains different concepts and provides practical examples of how they can it implements using real-world data sets from medical imaging datasets or public health records databases, among others. Furthermore, it offers insights into recent advances made by researchers which have enabled automated decision-making systems based on AI models with improved accuracy over traditional methods. This text also discusses ways through which current models could improve further by incorporating domain knowledge during the model training phase, thereby increasing their efficacy even further.Overall, this book serves as a great source of information about the latest advancements made in the field of Machine Learning & Artificial Intelligence towards efficient building systems capable enough detecting & diagnosing diseases automatically while avoiding human errors resulting due manual intervention at any stage along process pipeline thus ensuring better outcomes overall. Moreover, it helps readers understand the underlying principles behind each technique discussed so that they may apply them according to their own application scenarios efficiently without worrying much about the implementation details required to get the job done the right way the first time around itself! 404 pp. Englisch.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 149,79
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book 'Machine Learning for Disease Detection, Prediction, and Diagnosis' can be a comprehensive guide to the novel concepts, techniques, and frameworks essential for improving the viability of existing machine-learning practices. It provi…des an in-depth analysis of how these new technologies are helpful to detect, predict and diagnose diseases more accurately. The book covers various topics such as image classification algorithms, supervised learning methods like support vector machines (SVM), deep neural networks (DNNs), convolutional neural networks (CNNs), etc. unsupervised approaches such as clustering algorithms as well as reinforcement learning strategies.This book is an invaluable resource for anyone interested in machine-learning applications related to disease detection or diagnosis. It explains different concepts and provides practical examples of how they can it implements using real-world data sets from medical imaging datasets or public health records databases, among others. Furthermore, it offers insights into recent advances made by researchers which have enabled automated decision-making systems based on AI models with improved accuracy over traditional methods. This text also discusses ways through which current models could improve further by incorporating domain knowledge during the model training phase, thereby increasing their efficacy even further.Overall, this book serves as a great source of information about the latest advancements made in the field of Machine Learning & Artificial Intelligence towards efficient building systems capable enough detecting & diagnosing diseases automatically while avoiding human errors resulting due manual intervention at any stage along process pipeline thus ensuring better outcomes overall. Moreover, it helps readers understand the underlying principles behind each technique discussed so that they may apply them according to their own application scenarios efficiently without worrying much about the implementation details required to get the job done the right way the first time around itself!Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 404 pp. Englisch.
