A Review on Deep Learning Based Question Answering with Natural Language Processing in Healthcare

Over the Internet, an efficient approach and promising solution to retrieve significant information envisages the beginning of Question Answering Systems (QAS). Because of data sources availability, the deep learning model based on open domain QAS focuses a substantial quantity of research work. Because of the lack of medical datasets, less attention is received in the medical domain. The deep learning (DL) utility increases the development of huge data in the healthcare domain. In the past years, popularity has grown in hardware parallelism and quick data storage availability. The challenge, pipelines, and tasks involved in medical NLP and medical imaging deploy the existing review of research in this work. The medical NLP and imaging fields deploy DL structures with its extensive survey is presented here. Over all 39 research papers are collected for this survey analysis from the years 2017 to 2023. The diagnosis is enhanced with medical imaging, Natural language processing, and DL combination to detect the appropriate combination. Each of the outcomes is shown graphically. The information provided in this survey is quite useful for newcomers carrying out research in medical informatics.