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Record Nr. |
UNINA9910627260103321 |
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Titolo |
Artificial Intelligence and Machine Learning for Healthcare : Vol. 1: Image and Data Analytics / / edited by Chee-Peng Lim, Ashlesha Vaidya, Yen-Wei Chen, Tejasvi Jain, Lakhmi C. Jain |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (239 pages) |
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Collana |
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Intelligent Systems Reference Library, , 1868-4408 ; ; 228 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Biomedical engineering |
Artificial intelligence |
Medical informatics |
Computational Intelligence |
Biomedical Engineering and Bioengineering |
Artificial Intelligence |
Health Informatics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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An Introduction to Artificial Intelligence in Healthcare -- Radiomics: Approach to Precision Medicine -- Artificial Intelligence Based Strategies for Data-Driven Radial MRI. . |
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Sommario/riassunto |
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Artificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and well-being issues of humans. AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems, improving treatments and quality of care for patients. This edition on AI and ML for healthcare consists of two volumes. The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future. In this first |
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volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented. These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector. |
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