Conversational artificial intelligence development in healthcare

Conversational Artificial Intelligence (AI) has emerged as a promising technology in the healthcare domain, facilitating interactive and personalized interactions between patients, healthcare professionals, and virtual assistants. This abstract presents an overview of the development process for Conversational AI in healthcare, focusing on utilizing Recurrent Neural Networks (RNNs). RNNs are well-suited for sequence modeling tasks and enable context-aware responses. Conversations can be complex, and emotions expressed within them may not always be clear-cut. It can be challenging for sentiment analysis models to interpret accurately. To overcome these issues, create a novel technique called Generative Pretrained based Recurrent Neural Network (GPbRNN). The developed model is to increase the efficiency of the model and also improve the emotional predictions. Conversational AI in healthcare, empowered by RNNs, can revolutionize the field by providing personalized and accessible information to patients, supporting healthcare professionals in decision-making, and enhancing overall healthcare delivery. Further research and development in this area promise to improve patient outcomes and transform healthcare.