A New Era in Diagnosis: From Biomarkers to Artificial Intelligence, 2nd Edition
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 183
Special Issue Editors
Interests: medical research methodology; biostatistics; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Interests: medical research methodology; biostatistics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue reflects the experience of the editorial team over the past two years, which successfully concluded its first edition with no fewer than 19 published articles. We are now returning with a second edition because the field has a huge potential for development.
In recent years, it has become more important to look into new ways to diagnose diseases using biomarkers and artificial intelligence (AI). In fact, technologies like AI and machine learning might be able to change how cancer is diagnosed and treated, as well as find signs that can predict the future.
The Special Issue covers building multimodal machine learning, a branch of machine learning that focuses on creating and training models that can use different types of data, like genomic, proteomic, and imaging data, to make their performance more predictable. One of its benefits is that it can combine different types of info. For instance, imaging data can be turned into sound data so that some of the older systems could better tell the difference between cancerous and benign tumours. Putting together different types of clinical data into a single AI model is a big step toward making more complete images of clinical data.
AI helps combine different types of data, and there is also a big shift toward using digital data with numbers in clinical research, making use of the huge amounts of biomarker data created around the world. It has been found that AI, especially machine learning and high-performance computers, is the only way to combine very large datasets from genomics, proteomics, and other "omics" technologies. This change makes it possible to create new treatments and models that can predict how a drug will work. Instead of using just one biomarker, scientists can now use combinations of biomarkers to make better decisions about diagnosis and treatment.
In addition, most biomarker discovery for diseases has relied on using methodologies in AI toward obtaining predictive biomarkers or scores to accelerate the development of diagnosis and treatment. Using supervised and non-supervised machine learning algorithms while analyzing vast datasets without any bias is evident in the identification of novel biomarker candidates. Medicines for different illnesses have an unmet need for biomarker discovery, highlighting that AI will have a high impact in predictive diagnostics and therapeutic strategies.
These breakthroughs reinforce the critical role of AI and machine learning in enhancing understanding and capacity toward the proper diagnosis and treatment of diseases. These are necessary in an era of personalised medicine, in which data-driven insights steer health solutions into more accurate and effective directions.
Prof. Dr. Tudor Drugan
Dr. Daniel Leucuta
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 250 words) can be sent to the Editorial Office for assessment.
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. Diagnostics 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 2600 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
- biomarkers
- diagnosis
- personalized medicine
- therapeutic strategies
- artificial intelligence
- machine learning
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