Artif Intell Med 2022 May 2;127:102264. Epub 2022 Mar 2.
Université de Lyon, Lyon, France; Université Lyon 1, Villeurbanne, France; Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France; Équipe Biostatistique-Santé, Laboratoire de Biométrie et Biologie Évolutive, CNRS UMR 5558, Villeurbanne, France.
In a number of circumstances, obtaining health-related information from a patient is time-consuming, whereas a chatbot interacting efficiently with that patient might help saving health care professional time and better assisting the patient. Making a chatbot understand patients' answers uses Natural Language Understanding (NLU) technology that relies on 'intent' and 'slot' predictions. Over the last few years, language models (such as BERT) pre-trained on huge amounts of data achieved state-of-the-art intent and slot predictions by connecting a neural network architecture (e. Read More