AI-Based Medical Scribe to Support Clinical Consultations: A Proposed System Architecture

AI applications in hospital frameworks can improve patient-care quality and efficient workflows and assist in digital transformation. By designing Smart Hospital infrastructures, creating an efficient frame-work enables patient information exchange between hospitals, point of care, and remote patient monitoring. Deep learning (DL) solutions play important roles in these infrastructures' digital transformation process and architectural design. Literature review shows that DL solutions based on Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) are rising concerning clinical data digitalisation, population health management, and improving patient care. Nevertheless, one of the literature's shortcomings highlights the limited research using these solutions in real-world medical environments. As part of smart hospitals, smart medical scribes have been presented in several studies as a promising solution. However, just a few studies have tested it in real settings. Moreover, it was limited to non-existent studies on non-English systems, even yet to be found similar studies for European Portuguese. The proposed study evaluates NLP-based solutions in real-life Portuguese clinical settings focused on patient care for Smart Healthcare applications.