Computational Diagnostics

About the journal

Computational Diagnostics is a multidisciplinary, open-access journal for artificial intelligence, machine learning, and data-driven methods applied to healthcare, medicine, and clinical science. We publish research spanning the full pipeline, from algorithms and foundation models to clinical validation and real-world deployment, that advances diagnosis, prognosis, decision support, and patient outcomes.

All research articles undergo double-blind peer review by independent experts and are published open access under a CC BY 4.0 licence, with authors retaining copyright and a permanent DOI assigned on publication.

Aims & scope

Computational Diagnostics is a multidisciplinary international journal covering artificial intelligence, computational methods, healthcare, medicine, clinical science, digital health, medical technology, and data-driven research. It publishes work across the full pipeline, from fundamental methods and algorithms to clinical implementation and real-world health outcomes. The central connection is always computation, AI, data, healthcare, medicine, and clinical application.

Primary fields

• Artificial intelligence, machine learning, deep learning, generative AI, large language models, foundation models, multimodal AI, and AI agents
• Computer vision, natural language processing, data science, and computational science
• Digital health, health & medical & clinical informatics, and healthcare technology
• Clinical medicine, medical imaging, radiology, pathology, genomics, and molecular diagnostics
• Bioinformatics, computational biology, precision and personalized medicine, and drug discovery
• Public health, epidemiology, health services research, and biostatistics

Computational and AI applications

• Diagnosis, screening, early disease detection, prognosis, and clinical risk prediction
• Patient stratification, treatment selection, and clinical decision support
• Medical imaging, pathology, genomics, drug discovery, and clinical trials
• Patient monitoring, healthcare operations, population and precision healthcare

Emerging technologies

• Generative AI, LLMs, multimodal and vision-language models, foundation models, and AI agents
• Retrieval-augmented generation, explainable, trustworthy and responsible AI
• Federated and privacy-preserving learning, synthetic data, and digital twins
• Wearable AI, digital biomarkers, the Internet of Medical Things, and intelligent medical devices

Article types

Original Research, Systematic Reviews, Meta-Analyses, Scoping and Narrative Reviews, Methodological Research, Clinical Validation Studies, Computational and Data Studies, Benchmark Studies, Short Communications, Brief Reports, Protocols, Perspectives, Commentaries, and Editorials.