9781032367118 - Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine (27 risultati)

hardcover. Condizione: Fine. Open Books is a nonprofit social venture that provides literacy experiences for thousands of readers each year through inspiring programs and creative capitalization of books.

Condizione: New.

Hardcover. Condizione: new. Hardcover. This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care This title covers computer vision and machine learning (ML) advances that facilitate automation in diagnostic, therapeutic, and preventative healthcare. The book shows the development of algorithms and architectures for healthcare. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condizione: As New. Unread book in perfect condition.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: NEW.

Condizione: New.

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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Hardcover. Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Hardcover. Condizione: new. Hardcover. This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care This title covers computer vision and machine learning (ML) advances that facilitate automation in diagnostic, therapeutic, and preventative healthcare. The book shows the development of algorithms and architectures for healthcare. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condizione: NEW.

Condizione: New. 2023. 1st Edition. Hardcover. . . . . .

Condizione: New.

Hardback. Condizione: New. This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care.

Condizione: New.

Condizione: New. 2023. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Condizione: Brand New. 352 pages. 9.19x6.13x0.83 inches. In Stock.

Buch. Condizione: Neu. Explainable AI in Healthcare | Unboxing Machine Learning for Biomedicine | Mehul S Raval (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2023 | Chapman and Hall/CRC | EAN 9781032367118 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Hardback. Condizione: New. This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.This book will benefit readers in the following ways:Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health careInvestigates bridges between computer scientists and physicians being built with XAIFocuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparentInitiates discussions on human-AI relationships in health careUnites learning for privacy preservation in health care 330 pp. Englisch.

Hardcover. Condizione: Brand New. 352 pages. 9.19x6.13x0.83 inches. In Stock. This item is printed on demand.

Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering.This book will benefit readers in the following ways:Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health careInvestigates bridges between computer scientists and physicians being built with XAIFocuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparentInitiates discussions on human-AI relationships in health careUnites learning for privacy preservation in health care.