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SI MLMA 2014 : Special issue - Machine learning for medical applications for The Scientific World Journal


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Submission Deadline May 2, 2014

Call For Papers

Machine learning (ML) has been well recognised as an effective tool for researchers to handle the problems in signal and image processing. Machine learning is capable of offering automatic learning techniques to excerpt common patterns from empirical data and then make sophisticated decisions, based on the learned behaviours. Medicine has a large dimensionality of data and the medical application problems frequently make the human-generated, rule-based heuristics intractable. In this special issue, we provide a forum to present the cutting-edge machine learning methods for medical applications. Applications for medical application may include the learning of similarities across different image modalities, organ localization, learning of anatomical changes, tissue classification, and computer-aided diagnosis.

We invite authors to submit original research and review articles that seek to improve the quality of healthcare and medical diagnosis and treatment. Potential topics include, but are not limited to:

Artificial intelligence in medicine
Cardiovascular mechanics
Clinical interpretation and analysis
Decision support systems
Brain-computer interface
Biomedical and genomic signal processing
Hospital information system
Quantum computing and its applications in medicine
Medical image analysis and understanding
System biology in transitional medicine

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at according to the following timetable:

Manuscript Due Friday, 2 May 2014
Final Decision Date Friday, 30 May 2014
Publication Date Friday, 11 July 2014

Lead Guest Editor

Huiyu Zhou, School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, UK

Guest Editors

Jinshan Tang, School of Technology, Michigan Technological University, Houghton, MI, USA
Huiru Zheng, School of Computing and Mathematics, University of Ulster, Londonderry, UK

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