This special issue of ConductScience Journal focuses on emerging work at the intersection of digital health, wearable technologies, data science, and applied clinical artificial intelligence. The issue is intended for scholarly submissions that present meaningful contributions in areas such as predictive modeling, multimodal data integration, wearable sensor analytics, interpretable machine learning, clinical risk stratification, and technical pipeline development for healthcare applications.

We welcome papers that emphasize methodological innovation while maintaining strong clinical relevance. Appropriate submissions may include studies on symptom forecasting, physiologic phenotyping, digital biomarkers, benchmarking of machine learning approaches, healthcare data infrastructure, and tools designed to support clinical decision-making, patient monitoring, or translational health research.

Submissions should be prepared with clear academic framing, sufficient methodological detail, balanced discussion of limitations, and consideration of implementation in real-world clinical or health technology settings.

This special issue aims to highlight technically strong, clinically grounded, and forward-looking work that contributes meaningfully to the evolving landscape of digital medicine and healthcare innovation.