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Intelligent Data Analytics for Bioinformatics and Biomedical Systems

Korhan Cengiz (Hrsg.), Neha Sharma (Hrsg.), Prasenjit Chatterjee (Hrsg.)

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Naturwissenschaften, Medizin, Informatik, Technik / Sonstiges

Beschreibung

The book analyzes the combination of intelligent data analytics with the intricacies of biological data that has become a crucial factor for innovation and growth in the fast-changing field of bioinformatics and biomedical systems.

Intelligent Data Analytics for Bioinformatics and Biomedical Systems delves into the transformative nature of data analytics for bioinformatics and biomedical research. It offers a thorough examination of advanced techniques, methodologies, and applications that utilize intelligence to improve results in the healthcare sector. With the exponential growth of data in these domains, the book explores how computational intelligence and advanced analytic techniques can be harnessed to extract insights, drive informed decisions, and unlock hidden patterns from vast datasets. From genomic analysis to disease diagnostics and personalized medicine, the book aims to showcase intelligent approaches that enable researchers, clinicians, and data scientists to unravel complex biological processes and make significant strides in understanding human health and diseases.

This book is divided into three sections, each focusing on computational intelligence and data sets in biomedical systems. The first section discusses the fundamental concepts of computational intelligence and big data in the context of bioinformatics. This section emphasizes data mining, pattern recognition, and knowledge discovery for bioinformatics applications. The second part talks about computational intelligence and big data in biomedical systems. Based on how these advanced techniques are utilized in the system, this section discusses how personalized medicine and precision healthcare enable treatment based on individual data and genetic profiles. The last section investigates the challenges and future directions of computational intelligence and big data in bioinformatics and biomedical systems. This section concludes with discussions on the potential impact of computational intelligence on addressing global healthcare challenges.

Audience

Intelligent Data Analytics for Bioinformatics and Biomedical Systems is primarily targeted to professionals and researchers in bioinformatics, genetics, molecular biology, biomedical engineering, and healthcare. The book will also suit academicians, students, and professionals working in pharmaceuticals and interpreting biomedical data.

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Schlagwörter

Personalized Medicine, Medical Imaging Analysis, Disease Biomarkers, Bioinformatics, Drug Discovery, Clinical Decision Support, Computational Intelligence, Quantum Computing in Bioinformatics, Biomedical Systems, Predictive Analytics, Big Data Analytics, Machine Learning in Healthcare, Precision Healthcare, Healthcare Data Mining, Remote Patient Monitoring