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Deep Learning for Health Informatics

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 498

Special Issue Editors

Information School, The University of Sheffield, Sheffield S1 4DP, UK
Interests: trust formation in health information; information literacy; public health; health information overload
Special Issues, Collections and Topics in MDPI journals
Information School, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
Interests: chemoinformatics and machine learning model interpretation

Special Issue Information

Dear Colleagues,

In the last few years, healthcare organisations of all sizes and types have shown an increasing interest in how artificial intelligence, machine learning and, in particular, deep learning can support and provide better patient care and health outcomes.

Deep learning is a branch of artificial intelligence that is very quickly becoming transformative for healthcare, offering the possibility to analyse data with unprecedented speed and precision. Big data and ever-increasing computational power are the reality in which deep learning operates, hence opening the doors to a new and exciting research frontier.

Deep learning has had the potential of dramatically changing, for the better, the use of a wide range of medical and patient-facing applications including medical imaging (including, among others, X-ray, magnetic resonance imaging, computed tomography, microscopy and ultrasound), electronic health records and knowledge extraction, genomics, biosensors, online health communications, drug discovery and precision medicine. However, as captivating as these applications can be, they are still mostly at the pilot stage and, hence, at the start of deep learning’s role in healthcare analytics.

There are still many hindrances to the effective application of deep learning in healthcare, the main one being, somehow paradoxically, the lack of data, particularly in the case of rare and age-specific conditions, as higher numbers of training sets result in more accurate and stable models.

For this Special Issue, we encourage the submission of papers on the potential for future applications of deep learning approaches in all aspects of healthcare and health informatics. Papers focusing on how to improve human interpretability of deep learning models, and on model reliability, scalability, feasibility and security are particularly welcome. We also welcome submissions that cover FATE (fairness, accountability, transparency and ethics) considerations of the use of deep learning on health information. We will consider original research papers using different study designs, as well as systematic reviews and meta-analysis.

Dr. Laura Sbaffi
Dr. Wasim Ahmed
Dr. Antonio de la Vega de Leon
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Deep learning
  • health informatics
  • computing methodologies
  • machine learning
  • applied computing health informatics
  • data analytics in health informatics

Published Papers

There is no accepted submissions to this special issue at this moment.
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