Machine Learning‐Reinforced Noninvasive Biosensors for Healthcare

The emergence and development of noninvasive biosensors largely facilitate the collection physiological signals processing health-related data. utilization appropriate machine learning algorithms improves accuracy efficiency biosensors. Machine learning-reinforced are started to use in clinical practice, health monitoring, food safety, bringing a digital revolution healthcare. Herein, recent advances applied healthcare summarized. First, different types collected categorized Then adopted subsequent data introduced their practical applications reviewed. Finally, challenges faced by raised, including privacy adaptive capability, prospects real-time out-of-clinic diagnosis, onsite safety detection proposed.