From Data to Decisions: Deep Learning in Clinical Diagnostics
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 May 2026 | Viewed by 25
Special Issue Editor
Interests: machine learning; medical image analysis; natural language processing; software engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The exponential growth in healthcare data, coupled with advances in deep learning architectures, has created unprecedented opportunities to revolutionize clinical diagnostics. From radiology and pathology to genomics and wearable devices, healthcare professionals now have access to vast, complex datasets that exceed human analytical capacity. Deep learning offers the computational power to transform this data deluge into precise, actionable diagnostic insights, potentially improving patient outcomes while reducing healthcare costs and diagnostic delays. This Special Issue will highlight innovative deep learning methodologies that bridge the critical gap between raw clinical data and evidence-based diagnostic decisions. We welcome submissions of research demonstrating how deep learning can enhance diagnostic workflows, improve accuracy across medical specialties, and facilitate personalized medicine approaches. Our focus will be on clinically validated solutions that show clear pathways to real-world implementation and measurable patient impacts. Potential research areas include (but are not limited to) the following:
- Novel deep learning architectures for medical image analysis;
- Integrated diagnostic platforms combining imaging, laboratory, and clinical data;
- Automated diagnostic workflows and clinical decision support;
- Deep learning for rare disease identification and early cancer detection;
- Biomarker discovery through AI-driven data mining;
- Performance validation and clinical implementation studies;
- Interpretability and trust in AI diagnostic systems;
- Regulatory compliance and clinical deployment challenges.
Dr. Jianfu Li
Guest Editor
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. 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
- deep learning
- clinical diagnostics
- medical AI
- diagnostic accuracy
- clinical decision support
- medical imaging
- biomarker discovery
- healthcare implementation
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