Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data: Intelligent Data-Centric Systems
Editat de Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Parvathaneni Naga Srinivasu, Goncalo Marquesen Limba Engleză Paperback – 24 ian 2022
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
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Specificații
ISBN-13: 9780323857512
ISBN-10: 0323857515
Pagini: 294
Ilustrații: 220 illustrations (20 in full color)
Dimensiuni: 191 x 235 x 20 mm
Greutate: 0.51 kg
Editura: ELSEVIER SCIENCE
Seria Intelligent Data-Centric Systems
ISBN-10: 0323857515
Pagini: 294
Ilustrații: 220 illustrations (20 in full color)
Dimensiuni: 191 x 235 x 20 mm
Greutate: 0.51 kg
Editura: ELSEVIER SCIENCE
Seria Intelligent Data-Centric Systems
Cuprins
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
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