Artificial intelligence rapidly penetrates biomedical research and wearable health technology. Novel frameworks integrate self-supervised learning with embedded bio-signals for enhanced wearable data analytics. AI-driven models improve clinical gait analysis, cancer image predictive accuracy, and photo patterning designs. Computer vision and machine learning enable low-cost 3D plant leaf area estimation, boosting agricultural monitoring. Furthermore, optical matrix multipliers revolutionize imaging compression and decoding, underscoring AI's transformative impact on health and environmental monitoring.