Freshly Printed - allow 10 days lead
Couldn't load pickup availability
Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data
Presents the latest trends in data processing for risk analysis and innovation in the healthcare industry
Akash Kumar Bhoi (Edited by), Victor Hugo Costa de Albuquerque (Edited by), Parvathaneni Naga Srinivasu (Edited by), Goncalo Marques (Edited by)
9780323857512, Elsevier Science
Paperback / softback, published 24 January 2022
294 pages, 220 illustrations (20 in full color)
23.5 x 19 x 1.9 cm, 0.61 kg
Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making. This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning.
Section 1: Cognitive Technology for processing of Healthcare data 1. Cognitive technology in personalized Medicine/healthcare solutions 2. Cognitive technology for blend of personalized healthcare information with scientific data for better clinical risk analysis and healthcare innovation 3. Healthcare data encryption, data processing for the data acquired from smart sensors and approaches Section 2: Artificial Intelligence Approaches for Healthcare Industry 4. Artificial Neural Networks based approaches for computer-aided disease diagnosis and treatment 5. AI and Deep Learning for processing the huge amount of patient centric data that assists in clinical decisions 6. Pattern Recognition and Computer vision approaches for handling healthcare data 7. Applications of Recurrent Neural Networks, Generative Neural Networks, Ensemble methods, Weakly Trained Approaches towards Data associated with healthcare solutions Section 3: Evolutionary Algorithms for Healthcare Data Analysis 8. Optimization inspired by biological evolution for high dimensional data for forecasting of illness in advance like Cancer, Heart disease, Brain tumors 9. Swarm Intelligence and Evolutionary Algorithms in processing the Healthcare Data 10. Recent advancements in evolutionary algorithms for handling the information related to healthcare industry Section4: Computational Intelligence and soft computing models in processing the data related to healthcare industry 11. Natural computing and Unsupervised Learning Methods in healthcare data-centric operations 12. Soft Computing and Machine Learning Techniques for healthcare data analytics 13. Probabilistic approaches for minimizing the healthcare diagnosis cost through data-centric operations 14. Computational Intelligence in Human-machine interface (HMI) e.g. ECG, EEG, EMG, PCG and predictive data analysis
Subject Areas: Enterprise software [UFL], Medical bioinformatics [MBF]
