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This book uncovers stakes and possibilities offered by Computational Intelligence and Predictive Analytics to Medical Science. The main focus is on data technologies,classification, analysis and mining, information retrieval, and in the algorithms needed to elaborate the informations. A section with use cases and applications follows the two main parts of the book, respectively dedicated to the foundations and techniques of the discipline.
Applications of computational intelligence and predictive analytics in screening potential lead molecules toward COVID-19: scope of repurposed drugs
Classification and clustering algorithms in identifying patterns in medical science
IoT – a supportive system for solving issues related to medical monitoring
Bioheat transfer simulation during RFA
Supervised classification and clustering algorithms for spatiotemporal change analysis assessment of urban growth
Enabling data to develop an AI-based application for detecting malaria and dengue
Pertinence of signal processing techniques in EEG analysis
Fitness tracking diagnostics
Personal big data–directed policies hoard and scrutinize colossal health data from emerging technologies
Real-time patient health monitoring
Forecasting, visualization and analysis of COVID-19 in India using time series modeling
Noninvasive prediction techniques of diabetic retinopathy
Change vector analysis in relation to terrain parameters using temporal remote sensing satellite data
Cloud-based E-learning platforms
Computational intelligence for analysis of urban surface temperature over various urban land cover features
Predictive analysis of consumers’ perception and decision-making process toward e-healthcare services in India