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About MMMDA

The management of patients with complex disease such as cancer usually requires a multidisciplinary team approach, and each case is often discussed within a multidisciplinary team (MDT). Moreover, the results of medical examinations are also extremely complicated. For example, there are multiple sequences of Magnetic Resonance Imaging (MRI). Different image sequences have unique values for disease diagnosis. Thus, multi-modal medical data analysis is critically important for disease diagnosis. With the development of deep learning and multi-modal data analysis techniques, researchers focus on a wide variety of deep learning -based applications in medicine, such as organ or lesion segmentation in medical images, disease data analysis, etc. This workshop will present recent advances under the umbrella of multi-modal medical data analysis, including medical image processing (e.g., organ and lesion segmentation for MRI, CT, or Ultrasound images), medical text data mining, etc. They are all research hotspots and future direction in the artificial intelligence-assisted diagnosis. We will discuss the key problems, common formulations, existing methodologies, real industrial applications, and future directions in the above topics. Our workshop views not only come from the research field but also combine the real-world requirements and experiences in the industrial community. Therefore, this workshop will inspire audiences from both academia and industry and facilitate research in multi-modal medical data for medical big data analysis modeling.

Research Topics

Important URL

IEEE BigData 2022

Paper Submission

Program Schedule

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Important Dates

Submission Instructions

Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Papers must be clearly presented in English, up to 10 pages IEEE 2-column format, including tables, figures, references and appendixes, should be submitted via the conference workshop online submission system. We also encourage the submission of short papers (4-6 pages IEEE 2-column format), or abstract papers (up to 4 page IEEE 2-column format). Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (more instructions and templates can be downloaded from the conference website). All accepted papers will be included in the conference proceedings and published by the IEEE Xplore Digital Library (covered by the Engineering Index).

Formatting Instructions

IEEE Computer Society Proceedings Manuscript Formatting Guidelines

Committee Members

General Chair

Prof. Wendong Wang, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China

Program Chair

Dr. Bo Zhang, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China

Technical Program Committee

Prof. Xiuzhuang Zhou, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.

Prof. Zhineng Chen, School of Computer Science, Fudan University, Shanghai, China

Dr. Wu Liu, JD AI Research, Beijing, China

Dr. Zhenxiang Gao, Center for Artificial Intelligence in Drug Discovery, Case Western Reserve University, Ohio, USA

Dr. Zheng Song, Department of Computer and Information Science, University of Michigan-Dearborn, Michigan, USA

Dr. Zheng Zhang, School of Modern Post, Beijing University of Posts and Telecommunications, Beijing, China

Dr. Lingjun Zhang, School of Computer Science and Technology, Hangzhou Danzi University, Hangzhou, China

Dr. Hui Gao, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China

Previous information

MMMDA 2021