Special Session on
Computational Intelligence in Disease Diagnosis, Prediction, and Prevention
Aim and Scope
The aim of this special session is to bring together researchers, academicians, and professionals from the interdisciplinary field of computational intelligence, healthcare, and data science to explore innovative approaches, methodologies, and applications for advancing disease diagnosis, prediction, and prevention. The session will focus on the integration of computational intelligence techniques, such as machine learning, artificial intelligence, and data analytics, into healthcare systems to enhance the accuracy, efficiency, and effectiveness of disease-related decision-making processes. The topics include but not limited to:
- Optimising medical prediction problems using Swarm Intelligence
- Meta-Learning for Few-Shot Learning from medical images
- Transfer Learning applications in disease prediction using medical images
- Explainable AI in decision-making systems on treatment systems
- Federated Learning in electronic health record management
- Optimising Neural Networks with evolutionary algorithms
- Quantum Computing applications in the medical domain
- Reinforcement Learning in the medical decision-making system
- Generative Adversarial Networks in medical data analysis
- Mathematical modeling of electronic health record diagnosis
This special session aims to provide a platform for researchers and professionals to share their insights, latest research findings, and experiences in the application of computational intelligence in the healthcare domain, ultimately contributing to the advancement of disease diagnosis, prediction, and prevention.
Paper Submission
Potential authors may submit their manuscripts for presentation consideration through ICETCI 2024 submission system electronically at https://edas.info/N31894 , following the conference guidelines. All submissions will go through peer review process. To submit your paper to this special session, you have to choose our special session title on the submission page.
Important Dates
| Paper submission deadline: | Apr 15, 2024 |
| Paper acceptance notification date: | Jun 20, 2024 |
| Final paper submission and early registration deadline: | Jun 30, 2024 |
Organizers
Dr. Prasanalakshmi Balaji
College of Computer Science,
King Khalid University, KSA
Email ID: drsanaksa@gmail.com
Prasanalakshmi Balaji is a Professor in the College of Computer Science, King Khalid University, Saudi Arabia. She was a Postdoctoral Fellow in the Data Science Laboratory at the Industrial University of Ho Chi Minh City, Vietnam. She received a Ph.D. (2014) at the Research & Development Center, Bharathiar University, India. Prasanalakshmi is broadly interested in Neural Networks for Medical Imaging, Deep learning, Machine learning, Data Science, and the Internet of Things (IoT).
Her industrial research affiliations include being a research member of the Center for Artificial Intelligence at King Khalid University, and the Cancer Immunology Project at USERN. She is a founder of Medical Imaging Research Lab at SCRA, India.
Dr. S. Amutha,
School of Computer Science and Engineering
Vellore Institute of Technology, Chennai, India
Email ID: amuthabenziker@gmail.com
Dr. S. Amutha is an Assistant Professor in School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India. She completed PhD in Anna University in the department of Information and Communication under the guidance of Dr. S. S. Vinsley from Anna University, Chennai. She has published papers on Image processing and Deep Learning. She is a reviewer and editorial board member for few journals. She always look for an exposure to share and learn new technologies. She was appointed as Member of Program Committee as well as Session Chair for few International Conferences. She has delivered guest lectures on Learning Algorithms: Machine Learning to Deep Learning, Deep Learning in Data Science and Machine Learning in Medical Imaging. She has published a book on IoT.