International Conference on
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Special Session I: Health Informatics: Improving Healthcare Using Machine Learning Techniques
Machine Learning is one of the key technologies that is being currently used to perform predictive analytics tasks in the Healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays medical data is available in many different forms like MRI images, CT Scan images, EHR data, Test reports, histopathological data, Doctor Patient conversation data, etc. This opens up huge opportunities for the application of Machine Learning techniques, to derive data driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, Machine Learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data driven approach is not taken. With the help of Machine Learning systems, today it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, Machine Learning techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of Genomic data using Machine Learning is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which Machine Learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression. Our special session on “Health Informatics: Improving Healthcare Using Machine Learning Techniques” aims at attracting research works, to demonstrate the potential and the advancements of machine learning approaches to utilize healthcare centric and medical datasets.
Topics of interest include, but are not limited to:
- Clinical decision support systems
- Optimization of machine learning approaches applied to health-care
- Chronic disease management
- Medical Data mining
- Data Visualization for Healthcare Applications.
- Patient analytics
- Machine learning applications to healthcare
- Precision healthcare/ personalized healthcare
- Predictive Analytics on Medical Images
- Improving Patient Experiences Using Machine Learning
- Public Health Bioinformatics
- HEALTHCARE: Devices, Systems and Innovative Technologies
- AI wearable for healthcare
- Smart system for remote healthcare
- Integrated systems
- Electronic medical data
- Problems in health data processing
- Electronic health records and standards
- Pervasive Healthcare Information Systems and Services
- E-health Applications
- E-health solutions in India
Dr. Pinki Roy, National Institute of Technology Silchar
Email ID: pinkiroy2405@gmail.com
Prof. Pradip Kumar Das, Indian Institute of Technology Guwahati
Special Session II: Cognitive Informatics (CI)
Original and unpublished high quality research papers are solicited from the academicians, researchers and industry practitioners on traditional and advanced topics of cognitive informatics. Recommended topics include but are not limited to the following:
- Autonomous decision making
- Autonomous machine learning
- CI foundations of software engineering
- Cognitive agent technologies
- Cognitive foundation of big data
- Cognitive inferences
- Cognitive information fusion
- Cognitive knowledge bases
- Cognitive linguistics
- Cognitive modelling
- Cognitive models
- Cognitive sensors and networks
- Computing with words (CWW)
- Concept & semantic algebras
- Emotion modelling
- Emotion recognition
- Informatics models of the brain
- Machine consciousness
- Memory models of the brain
- Natural Language Processing
- Perception and thinking processes
Dr. Krishna Asawa (e-mail : krishna.asawa@jiit.ac.in)
Dr. Shikha Jain (e-mail shikha.jain@jiit.ac.in)
Jaypee Institute of Information Technology, Deemed to be University, Noida, India