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Special Issue on Computational Intelligence Methodologies in the Context of Recurrent Cancers: From Prediction to Prognosis

Mutants in Microgravity, USA, March 16, 2017 | © Courtesy of NASA's Marshall Space Flight Center/Flickr.
Mutants in Microgravity, USA, March 16, 2017 | © Courtesy of NASA's Marshall Space Flight Center/Flickr.

The journal Open Medicine invites submissions for its topical issue entitled “Computational Intelligence Methodologies Meets Recurrent Cancers – From Prediction to Prognosis.”


GUEST EDITORS

Chi-Chang Chang, Chung-Shan Medical University, Taiwan.
Tetsuya Sakurai
, University of Tsukuba, Japan.


DESCRIPTION

All cancers are usually classified according to the extent or stage of disease so that therapies may be tailored to the particular disease stage. In general, detection of asymptomatic recurrences is associated with prolonged overall survival and survival from the time of the initial detection of recurrence.

However, the treatments of recurrent cancers are still a complex clinical challenge. When the recurrence is not surgically resectable and/or suitable for curative radiation, therapeutic options are limited. With such complex situations, it can be difficult to assess all treatment options. Medical informatics as an interdisciplinary scientific field seeks to address that.

This research field is concerned with the development and application of advanced data processing methods in order to better understand and to improve healthcare, such as for cancer patients. Medical informatics can assist with the diagnosis, treatment, and prevention of cancers.

Thus, this special issue invites papers on the application of computational intelligence methodologies to cancer-related illness, injury, and physical and mental impairment treatments. This topical issue encompasses theoretical, practical, and technical issues spanning medical informatics and recurrent cancers.

Research on applications of prevention, prediction and prognosis topics are appropriate for this special issue. Practical experiences and experiments in using computational intelligence technologies and medical information technologies are also welcome. The editors of this topical issue look forward to contributions from academicians, researchers, and educators worldwide.


HOW TO SUBMIT

Please contact Guest Editor Dr Chi-Chang Chang threec@csmu.edu.tw and Managing Editor Magdalena Wierzchowiecka (Magdalena.Wierzchowiecka@degruyteropen.com) to let know about the submission of a paper to this topical issue.

Prospective authors are invited to feel free to register at the paper processing system of Open Medicine, to submit their papers: www.editorialmanager.com/openmed.

All papers will go through the review process of Open Medicine. It ensures high standards, as part of its fast, fair and comprehensive peer-review procedures.

Instructions for authors are available at the webpage of Open Medicine: www.degruyter.com/view/supplement/s23915463_Instruction_for_Authors.pdf

In case of any questions please contact Guest Editor (threec@csmu.edu.tw) or Managing Editor (Magdalena.Wierzchowiecka@degruyteropen.com).

Authors of Open Medicine benefit from:

  • transparent, comprehensive and fast peer review procedures;
  • efficiency en route to fast-track publication and a full advantage of De Gruyter’s e-technology platform;
  • free language assistance for authors from non-English speaking regions.

Edited by Pablo Markin


Featured Image Credits: Mutants in Microgravity, USA, March 16, 2017 | © Courtesy of NASA’s Marshall Space Flight Center/Flickr.


OpenEdition suggests that you cite this post as follows:
Pablo Markin (October 15, 2019). Special Issue on Computational Intelligence Methodologies in the Context of Recurrent Cancers: From Prediction to Prognosis. Open Access Blog. Retrieved December 10, 2024 from https://doi.org/10.58079/sh2d


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