A New Wave of Generative Flow Networks in Streaming Healthcare with Artificial Intelligence

AI in health care has proved significant due to generative flow networks’ ability to interpret, analyze and process all medical information for clinical use. Among the rising AI paradigms, the Generative Flow Networks (GFNs) have attracted much attention as they can capture complicated probability distributions and generate accurate data representations. GFNs use invertible neural networks to sample data effectively. This property allows them to solve intricate patterns with medical data such as images and genomic sequences making it suitable for stream processing in health care. This chapter introduces the new paradigms of the forthcoming predictive and diagnostic instruments and therapeutic technologies. Streaming healthcare data is being continuously captured from various sources apart from wearable devices and real-time imaging systems. Besides performing data processing, generative flow networks can extend their potential to change real patient care procedures by identifying individual patients and generating clinical decisions using AI. This capability is particularly applicable in areas where the detection of diseases at low incidence is accompanied with a large volume of data. Indeed, GFNs can create a chance for developing models to ensure patients’ privacy by generating and using fake patient records.