Artificial intelligence, preventive cardiology and making time for what matters: a fellow's voice.

The Research Topic “” was established to highlight emerging innovations and interdisciplinary advances at the intersection of Artificial Intelligence (AI) and healthcare. The contributions collected within this Research Topic encompass a broad range of themes, including explainable AI, AI-driven diagnostics, medical imaging analysis, multimodal data fusion, federated learning, mobile healthcare, intelligent clinical decision support systems, and precision medicine applications. Collectively, these studies demonstrate the expanding role of AI in enhancing healthcare quality, accessibility, efficiency, and personalization while also addressing important technical, ethical, and translational considerations. As illustrated in , the studies published in this Research Topic can be broadly organized into several major thematic research clusters, collectively reflecting the rapidly advancing and increasingly interdisciplinary nature of digital medicine and AI. The first thematic cluster focuses on AI-enabled diagnostics and medical imaging. Collectively, these studies demonstrate the growing maturity of AI-assisted diagnosis across multiple medical specialties. Rather than focusing solely on disease detection, they illustrate a transition toward quantitative image analysis (), explainable prediction, and clinically interpretable decision support. Representative examples include AI-assisted tuberculosis screening, ophthalmic (; ) image segmentation for meibomian gland dysfunction (), transformer-based thyroid ultrasound segmentation (), and AI applications in dermatology (). Nevertheless, external validation and prospective evaluation remain limited, highlighting important priorities for future clinical translation. The second thematic cluster centers on digital health interventions and AI-assisted chronic disease management. The randomized controlled trial conducted by evaluated an app-based multimodal digital intervention for individuals with type 2 diabetes. The longitudinal study by assessed one-year outcomes of automated insulin delivery systems in adults with type 1 diabetes. developed a mobile-based cognitive behavioral therapy intervention for anxiety and depression management in Mexico. These contributions collectively highlight the increasing importance of scalable, patient-centered, and real-world deployable digital healthcare technologies capable of supporting chronic disease monitoring, behavioral intervention, and personalized long-term healthcare management.