Artificial Intelligence and Deep Learning Models for Human Diseases Diagnosis and Prediction

Dear Colleagues, 

Artificial intelligence (AI) is profoundly transforming the methodologies and scope of medical research, from the investigation of disease mechanisms and biomarker discovery to innovation in therapeutic development and the analysis of complex biological systems. What were once theoretical computational approaches are now becoming pivotal research tools, driven by advances in data acquisition, computational power, and integrative analytics. This rapid progress simultaneously necessitates rigorous focus on methodological robustness, interpretability, and the translational pathway from model to biomedical insight. 

This Special Issue, “Artificial Intelligence and Deep Learning Models for Human Diseases Diagnosis and Prediction”, aims to provide a timely overview of emerging methodologies and future perspectives at the intersection of AI and foundational medical science. We seek contributions that not only present novel algorithms, models, or analytical frameworks but also critically examine their validity, generalizability, and potential to address specific biomedical research questions. Of particular interest are studies that leverage multimodal data to elucidate disease phenotypes, develop interpretable models for biological discovery, or propose innovative AI-driven research paradigms. 

We welcome original research articles and comprehensive reviews. Topics of interest include, but are not limited to:

• AI for disease mechanism discovery from imaging, pathology, and genomics data;
• Predictive modelling and pattern recognition in complex disease datasets;
• Foundation models and large language models for biomedical knowledge synthesis;
• Causal inference and robust AI for disease research;
• Multimodal data fusion and digital twin approaches for systems biology;
• AI-driven drug discovery and target identification;
• AI with robotics and automation for laboratory research;
• Validation, benchmarking, and reproducibility of AI methods in biomedical research. 

We look forward to receiving your contributions and to jointly shaping the future landscape of AI-driven medical research.

You may choose our Joint Special Issue in Life.

Dr. Mobarak I Hoque
Dr. Long Bai
Dr. Shilong Yao
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. Journal of Imaging 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 1800 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.

• artificial intelligence in medicine
• clinical decision support
• medical imaging
• precision medicine
• healthcare innovation
• trustworthy AI
• healthcare analytics
• predictive modeling
• digital health