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  • 1
    Online Resource
    Online Resource
    Prognostic Models in Healthcare: AI and Statistical Approaches (2022)
    Singapore : Springer Nature Singapore | Singapore : Imprint: Springer
    Details
    ISBN: 9789811920578
    Language: English
    Pages: 1 Online-Ressource(XXII, 504 p. 211 illus., 161 illus. in color.)
    Edition: 1st ed. 2022.
    Series Statement: Studies in Big Data 109
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Medical informatics. ; Computer simulation. ; Quantitative research. ; Neural networks (Computer science).
    Abstract: Segmentation of White Blood Cells in Acute Myeloid Leukaemia Microscopic Images: The Current Challenges and Future Solutions -- Computer Vision Based Prognostic Modeling of COVID-19 from Medical Imaging -- Skin Lesion Classification From Dermoscopic Images with Deep Residual Network based Fused Pigmented Deep Feature Extraction and Entropy Based Best Features Selection Approach -- Computer Vision Technologies for COVID-19 Prediction, Diagnosis and Prevention -- Health monitoring methods in heart diseases based on data mining approach, a directional survey -- Machine learning based brain diseases diagnosing in electroencephalogram signals, Alzheimer and Parkinson's -- Skin Lesion Detection Using Recent Machine Learning Approaches -- Improving monitoring and controling parameters for Alzheimer's patients based on IoT -- A Novel Method for Lung Segmentation of Chest with Convolutional Neural Network -- Leukemia Detection Using Machine and Deep Learning Through Microscopic Images-A Review.
    Abstract: This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry.
    DOI: 10.1007/978-981-19-2057-8
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    AI to Improve e-Governance and Eminence of Life : Kalyanathon 2020 (2023)
    Singapore : Springer Nature Singapore | Singapore : Imprint: Springer
    Details
    ISBN: 9789819946778
    Language: English
    Pages: 1 Online-Ressource(XII, 182 p. 118 illus., 108 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Big Data 130
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Political science. ; Computational neuroscience.
    Abstract: Artificial Intelligence for Rural Healthcare Management: Prognosis, Diagnosis and Treatment -- A Study using Support Vector Machine as a Tool for Patient’s Satisfaction for SARS-CoV-2 Cases Using Telemedicine -- Applications of AI and IoT technology in Protected Cultivation for Enhancing Agricultural Productivity: A Concise Review -- IoT Based Smart Farming Using AI -- Random Forest Algorithm for Plant Disease Prediction.
    Abstract: The volume presents research works on developing Artificial Intelligence based algorithms and methodologies for making social good that too to a notable one. The book discusses latest findings on efficient technological solutions of e-governance and other areas of life from the leading researchers in the field. The prime focus is on solving socio-economic technical problems using state-of-the-art research findings like fuzzy computing, evolutionary and hybrid frameworks, neuro computing, etc., along with other AI based computation platforms. The topics covered include solution frameworks using Artificial Intelligence based models in application areas like agriculture and rural development, road accident, travel and tourism, solid waste management, rural medical care, crowd sourced election monitoring system, ragging, rape and other abuses, cyber criminals and cyber bullying, disaster management, social good, etc. The book offers a valuable resource for all undergraduate, postgraduate students and researchers interested in exploring solution frameworks for social good problems using artificial intelligence.
    DOI: 10.1007/978-981-99-4677-8
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    BSZ
    MPI Ethno. Forsch.
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