posted by user: hponce || 1684 views || tracked by 7 users: [display]

WCCI-IJCNN SS 2024 : Special Session on Applied AI for Reliable and Trustworthy Medical Decision-Making Systems


When Jun 30, 2024 - Jul 5, 2024
Where Yokohama, Japan
Submission Deadline Jan 15, 2024
Notification Due Mar 15, 2024
Final Version Due May 1, 2024
Categories    artificial intelligence   medical systems   ethical ai   machine learning

Call For Papers

This is an accepted special session at

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

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.

- 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.


Related Resources

Ei/Scopus-AACIP 2024   2024 2nd Asia Conference on Algorithms, Computing and Image Processing (AACIP 2024)-EI Compendex
ICAASE 2024   The 6th Edition of the International Conference on Advanced Aspectsof Software Engineering
IEEE-Ei/Scopus-SGGEA 2024   2024 Asia Conference on Smart Grid, Green Energy and Applications (SGGEA 2024) -EI Compendex
SS-AAILH-HSI 2024   Special Session on Advances in artificial intelligence and learning in Healthcare
IEEE ICA 2022   The 6th IEEE International Conference on Agents
SAMLA 2024   Special Session on Applied and Theoretical Linguistics
AAAI 2025   The 39th Annual AAAI Conference on Artificial Intelligence
ICMLA 2024   23rd International Conference on Machine Learning and Applications
SS@CSNDSP 2024   Special Session on Reconfigurable Intelligent Surfaces for Communications and Sensing @ CSNDSP2024
IEEE Big Data - MMAI 2024   IEEE Big Data 2024 Workshop on Multimodal AI (Hybrid)