Description
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.- Focuses on data-centric operations in the Healthcare industry- Provides the latest trends in healthcare data analytics and practical implementation outcomes of the proposed models- Addresses real-time challenges and case studies in the Healthcare industry
Table of Contents
Section 1: Cognitive Technology for processing of Healthcare data 1. Cognitive technology in personalized Medicine/healthcare solutions2. Cognitive technology for blend of personalized healthcare information with scientific data for better clinical risk analysis and healthcare innovation3. Healthcare data encryption, data processing for the data acquired from smart sensors and approachesSection 2: Artificial Intelligence Approaches for Healthcare Industry4. Artificial Neural Networks based approaches for computer-aided disease diagnosis and treatment5. AI and Deep Learning for processing the huge amount of patient centric data that assists in clinical decisions6. Pattern Recognition and Computer vision approaches for handling healthcare data7. Applications of Recurrent Neural Networks, Generative Neural Networks, Ensemble methods, Weakly Trained Approaches towards Data associated with healthcare solutionsSection 3: Evolutionary Algorithms for Healthcare Data Analysis8. Optimization inspired by biological evolution for high dimensional data for forecasting of illness in advance like Cancer, Heart disease, Brain tumors9. Swarm Intelligence and Evolutionary Algorithms in processing the Healthcare Data10. Recent advancements in evolutionary algorithms for handling the information related to healthcare industrySection4: Computational Intelligence and soft computing models in processing the data related to healthcare industry11. Natural computing and Unsupervised Learning Methods in healthcare data-centric operations12. Soft Computing and Machine Learning Techniques for healthcare data analytics13. Probabilistic approaches for minimizing the healthcare diagnosis cost through data-centric operations14. Computational Intelligence in Human-machine interface (HMI) e.g. ECG, EEG, EMG, PCG and predictive data analysis
