Artificial intelligence (AI) and machine learning (ML) are rapidly transforming clinical and translational research by enabling the extraction of meaningful insights from complex biomedical and healthcare data. From disease diagnosis and prognosis to treatment response prediction and precision medicine, AI-driven approaches are reshaping how scientific discoveries are translated into clinical practice.

This Special Issue, “AI and Machine Learning in Clinical and Translational Research” aims to provide a platform for innovative research that advances the development, validation, and implementation of AI technologies across the translational research continuum. We welcome contributions addressing methodological advances, real-world clinical applications, and the integration of multimodal data sources, including omics, imaging, electronic health records, wearable devices, and other biomedical data.

Topics of interest include predictive modelling, clinical decision support systems, digital pathology, clinical bioinformatics, reproducible workflows, deep learning, explainable and trustworthy AI, federated learning, multimodal data fusion, AI-assisted diagnostics, and translational applications that facilitate personalized and precision medicine. Studies focusing on model interpretability, robustness, validation, regulatory considerations, and clinical implementation are particularly encouraged.

By bringing together researchers, clinicians, data scientists, and industry experts, this Special Issue seeks to highlight cutting-edge developments, foster interdisciplinary collaboration, and accelerate the responsible adoption of AI technologies that improve patient care and healthcare outcomes.

We look forward to receiving your valuable contributions.