A type of generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.
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Building a Conversational Chatbot Using Machine Learning: Towards a More Intelligent Healthcare Application
Ram Kumar Solanki (Sandip University, Nashik, India), Anand Singh Rajawat (Sandip University, Nashik, India), Amit R. Gadekar (Sandip University, Nashik, India), and Manoj Eknath Patil (SSBT's College of Engineering and Technology, Bambhori, India)
Copyright: © 2023
|Pages: 25
DOI: 10.4018/978-1-6684-7164-7.ch013
Abstract
The healthcare industry is facing numerous challenges in providing efficient and effective care to patients, including increased demand, limited resources, and a growing shortage of healthcare providers. To address these challenges, many healthcare organizations are turning to technology, specifically artificial intelligence (AI) and machine learning (ML), to improve patient care and outcomes. In response, the development of smart chatbots has emerged as a promising solution in the healthcare field. This chapter focuses on the design and implementation of a smart chatbot using AI and ML for healthcare applications. The main goal of the chatbot is to provide a more convenient and accessible method of delivering healthcare information and services to patients. This chapter will also explore the various components and algorithms used in the design of the chatbot, as well as its potential impact on the healthcare industry. Overall, this chapter demonstrates the value of AI and ML in healthcare and encourages further exploration and development of chatbots for healthcare applications.