Artificial Intelligence in Diagnostics: From Algorithms to Clinical Impact
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 March 2026 | Viewed by 28
Special Issue Editors
Interests: computer vision; Natural Language Processing (NLP); generative AI in healthcare; Large Language Models (LLM); multimodal AI; medical imaging
Interests: disease prediction; cancer typing; explainable AI; federated learning; social-emotion detection
Interests: AI in healthcare; explainable AI; medical imaging analysis; multi-modal fusion models; computer vision for healthcare; metric learning
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) is rapidly transforming the landscape of diagnostic medicine, offering unprecedented opportunities to derive intelligent, data-driven insights across clinical workflows. With the advent of powerful methodologies such as self-supervised learning, foundation models, and generative AI, healthcare is undergoing a paradigm shift—enabling earlier disease detection, more accurate prognoses, and personalized care at scale.
This Special Issue, "Artificial Intelligence in Diagnostics: From Algorithms to Clinical Impact," invites high-quality contributions that explore the latest AI and machine learning methodologies, with a strong emphasis on real-world clinical deployment and translational relevance. We especially welcome interdisciplinary work that integrates diverse data modalities, emphasizes transparency and fairness, and tackles the challenges of validation and implementation in clinical settings.
Topics of interest include, but are not limited to, the following:
- Disease diagnosis, prognosis, and risk prediction using AI;
- Multimodal learning from clinical, imaging, and genomic data;
- Self-supervised learning and foundation models in diagnostics;
- Generative AI for medical data synthesis and augmentation;
- Deep learning applications in medical imaging, histopathology, and biosignals;
- Natural language processing for electronic health records (EHRs), clinical notes, and patient communication;
- Explainability, fairness, and trust in clinical AI systems;
- Federated learning and privacy-preserving diagnostic AI;
- Benchmarking, validation, and regulatory frameworks for AI in medicine.
Topics of interest potentially also include the following:
- Improved methods and technical pipelines for privacy-preserving data synthesis, including different data formats such as EHRs and medical images;
- Easy-to-use and configurable data services to enable AI developers’ access to larger pools of decentralized de-identified data through multi-party computing.
We welcome original research articles, impactful case studies, and comprehensive reviews that bridge theoretical innovation with clinical outcomes. This Special Issue serves as a platform for meaningful exchange between researchers, clinicians, data scientists, and healthcare innovators committed to shaping the future of AI-powered diagnostics.
We look forward to hearing from you.
Dr. Ali Athar
Prof. Dr. David Brown
Guest Editors
Dr. Hanem Ellethy
Guest Editor Assistant
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
- machine learning in healthcare
- artificial intelligence in diagnostics
- medical imaging and deep learning
- generative AI in medicine
- multimodal data integration
- explainable and trustworthy AI
- translational medical AI
- clinical decision support systems
- secure and privacy-compliant data utilization
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