Automation of the Analysis of Medical Interviews to Improve Diagnoses Using NLP for Medicine

In the face of the dynamic advancements in health technology, the introduction of Natural language processing (NLP) into medical interviews represents an innovative approach influencing the diagnostic process and patient care. This article introduces a novel algorithm that leverages NLP to automate the analysis of medical texts, enabling the effective classification of patient symptoms and the identification of relationships between these elements. We delineate the contextual analysis process, including an example of the algorithm’s application in identifying potential respiratory system issues based on descriptions from conducted medical interviews with patients. Through a case study, we illustrate the practical application of the algorithm, evaluating the obtained results. Finally, we present perspectives on the development of this innovative approach in the context of future research and potential applications in the healthcare domain.