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Smart healthcare systems /

About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical infor...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Sinha, Adwitiya (Editor ), Rathi, Megha (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : CRC Press, [2020]
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Smart healthcare systems /  |c edited by Adwitiya Sinha and Megha Rathi. 
264 1 |a Boca Raton :  |b CRC Press,  |c [2020] 
300 |a 1 online resource (xiii, 233 pages) :  |b illustrations 
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504 |a Includes bibliographical references and index. 
520 |a About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions. 
545 0 |a Dr. Adwitiya Sinha received her PhD from Jawaharlal Nehru University (JNU), New Delhi. She is a recipient of a Senior Research Fellowship from CSIR, New Delhi, India and a UGC Research Scholarship. Her application-based research is mainly focused on large-scale graphs, data analytics, and confluence of sensor-based applications with social networking. Megha Rathi has 10 years of teaching experience. She has worked on the Xform generator research project of at NIC, Delhi. She has experience in software development and worked as a Project Associate at IIT Delhi. Her research areas include Data Mining, Data Science Analytics, Health Science, and Machine Learning. 
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700 1 |a Sinha, Adwitiya,  |e editor. 
700 1 |a Rathi, Megha,  |e editor. 
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