CLOSED Call for Papers: Special Issue on Transfer Learning Methods Used in Medical Imaging and Health Informatics

Due to the extensive use of various medical information systems, large quantities of medical data and clinical information (such as multi-modal medical images and standard electronic medical records) have been collected in many hospitals and institutes. Most existing analysis methods, however, use these data separately, ignoring the relationship among potentially related categories of medical data. Transfer learning, as one countermeasure capable of improving the process performance on a target data set (target domain) by using the beneficial information acquired from other associated data sets (source domains), is worthy of deep use in medical applications. This is good at improving the accuracies of clinical diagnoses as well as medical decisions. Also, methods based on transfer learning are able to boost the service quality as well as competitive advantage of hospitals to a great extent. This special issue focuses primarily on novel theories and methods using transfer learning proposed for medical imaging and health information processes, such as the transfer classification, transfer clustering, transfer regression, and transfer deep learning-based methods. Our purpose is to review the new progress and achievements on transfer learning and their applications in medical imaging and health informatics in recent years. Topics of interest for this special issue include, but are not limited to: - Transfer learning in clinical imaging process and analysis - Transfer learning in medical signal processing - The clinical decision support system (CDSS) - Intelligent health management - Precision medical treatment - Data mining based on electronic medical records - Comparative effectiveness research - Regional disease surveillance - Transfer learning in clinical treatment decision - Social media analysis for health using transfer learning - Mental health data analytics - Social media and intelligent sensing blog platforms - Advanced transfer learning algorithms and models

Schedule

Paper submissions due: CLOSED First notification: Dec. 31, 2019 Revision due: Feb. 28, 2020 Final decision: June 30, 2020 Publication date: in 2020

Guest editors

(1) Liu LIU, Nanjing University of Posts and Telecommunications, China. Email: liuliu.njupt@hotmail.com (2) Reza Zare, Department of Informatics, University of Leicester, UK. Email: mrz3@leicester.ac.uk (3) Shuihua WANG, School of Architecture Building and Civil Engineering, Loughborough University, UK. Email: shuihuawang@ieee.org