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 approaches
Section 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 solutions
Section 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 industry
Section4: 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
