The development of data science approaches, which are widely employed in numerous domains of fundamental science research, has been greatly aided by the explosion of data to be processed (the big data era) and the availability of high-performance computing resources. The automation of procedures and the vast amount of data c reated an environment that was conducive to the use of artificial intelligence, and specifically machine learning techniques.
Over the past few years, the scientific community has paid close attention to the application of Data Science and AI in healthcare. By the end of 2022, there was over 45,000 medical mobile apps available on the Apple App Store and more than 54,000 healthcare and medical apps on the Google Plays Store. Through medical diagnosis and forecasting, it has been demonstrated both theoretically and empirically that multiple models perform noticeably better than single base models.
The purpose of this special session is to recognize and investigate the current issues in medical applications created with data science and artificial intelligence (machine learning in particular) techniques. Investigating the real-world challenges of implementing these models and their intrinsic drawbacks in relation to issues in effectively explainable artificial intelligence is another objective. The actual implementation of such systems for healthcare and related medical applications, as well as recent advancements in the underlying technology, will also be covered in this session.
The scope of the session includes, but is not limited to, the following topics:
- Applications of Data Science in Healthcare
- Healthcare Analytics with improved Multimedia Data Analytics
- Social Media Analysis for Healthcare applications
- Internet of things applied in healthcare field
- Healthcare and Big Data Analytics
- The use of artificial Intelligence to handle pandemic situations
- Machine and Deep Learning for drug discovery and Medical Care
- Mobile Health with remote access, security and Privacy Issues
- Mobile Portals and Telemedicine
- Computational intelligence in clinical medical science
- AI-based medical decision support systems
- Natural Language Processing in medical science
- Data analytics and mining for biomedical decision support
- Genomic and proteomic data analysis
- AI-based modeling and management of healthcare data and clinical processes
- Biomedical image analysis, Security and authentication
- Computational platforms and models for biomedicine
- Automatic disease prediction and diagnosis support systems
- Patients monitoring with real-time systems
- Protection and security of personal health data, electronic health records and standards
- Medical Image Health care solutions for specially-abled
- Health Informatics and Process management
- Authentication of healthcare data (e-health/m-health/telemedicine)
- Intelligent information systems for healthcare
