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Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI) / edited by Aditya Khamparia, Deepak Gupta, Ashish Khanna, Valentina E. Balas

Contributor(s): Khamparia, Aditya, editor literario | Gupta, Deepak, editor literario | Khanna, Ashish, editor literario | Balas, Valentina E, editor literario
Material type: materialTypeLabelE-bookSeries: (Intelligent Systems Reference Library, 1868-4408; 222).Publisher: Singapore : Springer International Publishing, 2022Edition: First edition 2022.Description: 1 recurso en línea (XV, 137 páginas) : 73 ilustraciones, 63 ilustraciones a color.ISBN: 9789811914768.Subject: Ingeniería biomédica -- Proceso de datos | Inteligencia artificial en medicinaOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Optimal Boosting Label Weighting Extreme Learning Machine for Mental Disorder Prediction and Classification -- Modeling of Explainable Artificial Intelligence with Correlation based Feature Selection Approach for Biomedical Data Analysis -- Explainable machine learning model for diagnosis of Parkinson disorder -- Explainable Artificial Intelligence with Metaheuristic Feature Selection Technique for Biomedical Data Classification -- Explainable AI in Neural Networks using Shapley Values -- Design of Multimodal Fusion based Deep Learning Approach for COVID-19 Diagnosis using Chest X-Ray Images.
In: Springer Nature eBookSummary: The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería R857.D34 2022 EB (Browse shelf(Opens below)) Acceso electrónico
Total holds: 0

Optimal Boosting Label Weighting Extreme Learning Machine for Mental Disorder Prediction and Classification -- Modeling of Explainable Artificial Intelligence with Correlation based Feature Selection Approach for Biomedical Data Analysis -- Explainable machine learning model for diagnosis of Parkinson disorder -- Explainable Artificial Intelligence with Metaheuristic Feature Selection Technique for Biomedical Data Classification -- Explainable AI in Neural Networks using Shapley Values -- Design of Multimodal Fusion based Deep Learning Approach for COVID-19 Diagnosis using Chest X-Ray Images.

The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies.

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