International Workshop on Transfer Learning Methods Used in Medical Imaging and Health Informatics (TL-MIHI 2020)
Chairs of the Workshop: Prof. Pengjiang Qian, Jiangnan University, China
Prof. Yuan Liu, Jiangnan University, China
Dr. Yizhang Jiang, Jiangnan University, China
Dr. Kaijian Xia, China University of Mining and Technology; Changshu No.1 People’s Hospital, China
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 accuracy 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.
The accepted papers will be published in the proceedings of ICMTEL 2020 – 2nd EAI International Conference on Multimedia Technology and Enhanced Learning, Springer’s Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
Areas of interest 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|
As in previous years, the conference intends to attract research community from around the world. Each submission will be reviewed by at least three independent experts.
Submission deadline: 1 October 2019
Authors’ notification: 2 December 2019
Camera-ready deadline: 20 January 2020
Conference dates: 10 April 2020
All registered papers will be published together with ICMTEL Proceedings by Springer and made available through SpringerLink Digital Library.
ICMTEL proceedings are subjected for indexing in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).
Additional publication opportunities in journals are being discussed.
Papers should be submitted through EAI ‘ConfyPlus‘ system, and have to comply with the Springer format (see Author’s kit section). Papers should be in English. Regular papers should be no more than 20 pages LNCS format.
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 will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation.
Paper review will be double-blind in order to avoid bias. Previously published work may not be submitted, nor may the work be concurrently submitted to any other conference or journal. Such papers will be rejected without review. The paper must start with a title, an abstract, and keywords.
Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work.