Artificial Intelligence and Biosensors in Healthcare and its Clinical Relevance: A Review

Data generated from sources such as wearable sensors, medical imaging, personal health records, pathology and public organizations have resulted in a massive information increase the sciences over last decade. Advances computational hardware, cloud computing, Graphical Processing Units (GPUs), Tensor (TPUs), provide means to utilize these data. Consequently, many Artificial Intelligence (AI)-based methods been developed infer large healthcare Here, we present an overview of recent progress artificial intelligence biosensors life sciences. We discuss role machine learning precision medicine, for Internet Things (IoT). review most advancements biosensing technologies that use AI assist monitoring bodily electro-physiological electro-chemical signals disease diagnosis, demonstrating trend towards personalized medicine with highly effective, inexpensive, precise point-of-care treatment. Furthermore, advances computing technologies, accelerated intelligence, edge federated data, are also documented. Finally, investigate challenges data-driven approaches, potential issues IoT-based generate, distribution shifts occur among different data modalities, concluding future prospects.