Deep Learning for Healthcare Applications and Analysis
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 3563
Special Issue Editors
Interests: business analytics & data mining; deep leaning; artificial intelligence applications; big data research; reliability prediction; six-sigma; quality & reliability engineering
Special Issue Information
Dear Colleagues,
Deep learning (DL) helps to construct efficient methods to learn the low-level structure of original data to obtain more intellectual descriptions, implicitly capturing complicated relations and features of large-scale input. In recent years, both theory development and practical applications of deep learning have significantly renovated healthcare areas. Due to the large-scale medical data that currently exist and the vast potential of deep learning, this field's state of the art has become a high-level research hot spot, outperforming conventional methods.
Despite the promising results obtained using deep learning, several unsolved challenges remain in relation to the clinical application of deep learning to healthcare. Some critical issues involved are data volume, quality, temporality, domain complexity, and interpretability.
These challenges introduce numerous chances and opportunities for future research to advance the field. Therefore, with this in mind, some of the identified promising future directions of deep learning in healthcare are: feature enrichment, federated inference, model privacy, incorporating expert knowledge, temporal modeling, and interpretable modeling. These future directions are considered in this Special Issue, with possible significant solutions.
Manuscripts, including high-quality research articles and critical reviews, are welcome for submission to this Special Issue on “Deep Learning for Healthcare Applications and Analysis”.
Topics of interest for this Special Issue include, but are not limited to:
- Medical imaging and diagnostics;
- Electronic health records analysis;
- Genomics data analysis;
- Drug discovery;
- Simplifying clinical trials;
- Personalized treatment;
- Improved health records and patient monitoring;
- Health insurance and fraud detection;
- Temporal healthcare data analysis.
Dr. Bharatendra Rai
Dr. S.A. Senthil Kumar
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. Algorithms 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 1600 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.
