Predictive Modeling in Biomedical Data Mining and Analysis

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Predictive Modeling in Biomedical Data Mining and Analysis
Περιγραφή: Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information. - Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification - Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks - Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications
Συγγραφείς: Sudipta Roy, Lalit Mohan Goyal, Valentina Emilia Balas, Basant Agarwal, Mamta Mittal
Resource Type: eBook.
Θέματα: Data mining, Medical informatics--Data processing, Biomedical engineering--Data processing
Categories: SCIENCE / Biotechnology, TECHNOLOGY & ENGINEERING / Biomedical
Βάση Δεδομένων: eBook Index
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DbLabel: eBook Index
An: 3051887
RelevancyScore: 962
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PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 962.24267578125
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  Data: Predictive Modeling in Biomedical Data Mining and Analysis
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  Data: Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information. - Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification - Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks - Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications
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RecordInfo BibRecord:
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        Scheme: ddc
        Type: prePub
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      – Code: eng
        Text: English
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      – SubjectFull: Medical informatics--Data processing
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      – SubjectFull: Biomedical engineering--Data processing
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
            – D: 15
              M: 06
              Type: profile
              Y: 2023
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              Value: 9780323914451
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