This is an accepted special session at

IEEE World Congress on Computational Intelligence (WCCI)
International Joint Conference on Neural Networks (IJCNN)


DESCRIPTION:
The advent of the big data era in healthcare comes with the widespread capture of health data in various forms, such as electronic patient records, administrative claim records, biometric data, sensor data, and medical images. Artificial Intelligence and machine learning techniques have been widely used to unlock the hidden value from the sophisticated data and transform them into sensible decision-making and actions to support better healthcare. There are many successful healthcare applications leveraging the power of AI. For example, the giant Google has partnered with healthcare organizations to successfully develop machine learning-enabled imaging and diagnostics tools for skin, eye diseases and lung, breast cancers and so on to support medical specialists’ better decision-making.


Nevertheless, the challenges of AI for healthcare are equally significant. For example, many practical issues, such as low-quality training data, model black box problems, algorithmic bias and unfairness, and data privacy issues, may undermine the existing solutions’ ability and hold them back from being integrated into the current healthcare systems. Only if these practical challenges are overcome can the adoption of AI grow further to genuine applications to transform healthcare.


This special session aims to showcase the recent advancements in applied AI to address emerging challenges and dilemmas, and deliver reliable and trustworthy intelligent systems in healthcare and medicine. It will also provide a global platform to share and discuss the latest research findings in achieving patient-centered and outcome-driven effective healthcare applying AI.

TOPICS:
- Contributions are expected to be related, but not limited, to the following topics:
- AI-driven medical decision support
- Biomedical and health informatics
- Computer-aided disease detection, diagnosis, and prognosis
- Public health informatics
- Explainable AI in healthcare
- Fuzzy modeling for intelligent healthcare
- Advanced neural network architectures in healthcare applications
- Transfer learning, multitask learning and multi-view learning in healthcare
- Machine learning and deep learning-driven approaches for medical imaging, ECG, EMG, EEG data, etc.
- Natural language processing in medical science
- Real-time neural networks for patients monitoring
- Privacy-aware AI architectures in healthcare, including decentralized approaches (e.g. federated learning)


All accepted papers will be jointly published within the main conference proceedings and they will be included on the IEEEXplore library.

PLEASE VISIT OUR DEDICATED WEBSITE FOR FURTHER DETAILS.