Machine Learning in Medicine and Health: Data, Methods and Applications
A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Artificial Intelligence in Medicine".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 92
Special Issue Editors
Interests: data analysis; machine learning; data mining; web usage mining
Special Issues, Collections and Topics in MDPI journals
Interests: microbiome; genomics; RNA; river ecology
2. Pediatric Research Team, Clinical Pediatric Hospital, 550166 Sibiu, Romania
Interests: data mining; data analysis; machine learning; network analysis; data visualization; sustainable development; entrepreneurship; bibliometrics
Special Issue Information
Dear Colleagues,
Technological advances in different domains, including medicine, have generated vast and variate/complex healthcare data: demographics and clinical data; diagnoses, procedures, and medication-related information; laboratory tests; medical images data; omics-data; IoT/mHealth/app/sensor data; social media data; free text; speech data, etc. Handling these multidimensional structured/semi/unstructured data is challenging and requires the joint effort of specialists with different backgrounds (biology, physics, computer science, mathematics, engineering, etc.). Artificial intelligence and machine learning methods and tools can assist practitioners in converting these data into knowledge in order to improve health quality.
This Special Issue aims to present research on the application of supervised/unsupervised/semi-supervised machine learning approaches in different areas of the medicine and health sciences sectors, giving insights into the following: data collection, organization, and preprocessing; research design and study hypothesis; machine learning analysis methods, application, validation, performance, and interpretation; and the complexity, advantages, limitations, and challenges of application in practice. These resources could provide support for physicians/health care professionals, researchers, and students about how these data-driven methods could be applied to clinical practice and/or further research.
This Special Issue invites original research and review articles on the applications of machine learning in different areas of the medicine and health sciences to present researchers’ personal experiences with a wide array of machine learning methods.
We look forward to receiving your contributions.
You may choose our Joint Special Issue in Applied Sciences.
Dr. Grażyna Suchacka
Guest Editor
Dr. Ioana Boeraş
Dr. Ionela Maniu
Guest Editor Assistants
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. Healthcare is an international peer-reviewed open access semimonthly 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 2700 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
- machine learning
- laboratory (bio)markers
- risk factors/risk scores
- classification
- prediction
- (disease) profiling
- diagnosis
- prognosis
- artificial intelligence
- medicine
- bioinformatics
- bibliometric
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