Special Session "Machine Learning for Medical Data Analysis" on IEEE SMC2023

Session Code: 42ntx

Information: 

Aiming to quantify the patient’s health status or discover the disease stage, medical data can be defined as a type of information obtained from patients, including images, sounds, electronic signals, health records, case studies, and so on. With rapid development and progress, Machine Learning (ML) especially Deep Learning (DL) has witnessed significant popularity in medical data analysis and produced a remarkable impact. Despite recent advances in ML or DL research, the intractable problem related to how to learn better representations of medical data still remains, for example, using supervised learning or unsupervised learning, how to fuse information from different types of medical data. In addition, most deep learning models require a large number of training samples, but the amount of medical data is usually insufficient, how to handle this case becomes an important research area. Moreover, the interpretability of the DL model is also a prominent topic for medical data analysis, since the “black-box” structures of DL models are difficult for people to understand.

This special issue aims to seek the original contributions of pioneer researchers toward addressing the abovementioned key problems and issues. We only accept submissions related to machine learning for medical data analysis. The topics of interest include (but are not limited to):

• Large-scale medical data pre-train algorithm
• Novel medical datasets, tasks and evaluation metrics.
• The novel model design for medical data analysis
• Un/Semi/weakly supervised learning for medical data analysis
• Domain adaptation, transfer learning for medical data analysis
• The multi-modal medical data fusion algorithm
• Interpretability of the medical data analysis algorithm
• Machine learning for healthcare
• Machine Learning for Medical Decision
• Applications in medical image reconstruction, super-resolution, segmentation and others.

IEEE SMC 2023 (CCF C類)

https://ieeesmc2023.org/

Please note that all special session papers will be reviewed like regular papers; the program committee will take care of the reviews.