Natural Language Processing and Its Contributions in Healthcare: State of the Art

Since its beginning, Natural language processing (NLP) had focused on representing and analyzing human language computationally. Its applications are expanding in various fields such as machine translation, email spam detection, Sentiment Analysis, summarization, medicine, question answering, etc. In this paper, we first present an overview of natural language processing. Then we discuss the role of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) in the field of NLP, presenting their architectures, features and their limitations that have led to the development of a more advanced architecture: the transformer. Next, we delve into the Large Language Models presentation. Finally, we give insights into NLP applications in the medical field.