Artificial Intelligence Decision Support for Medical Triage
This addresses the need for efficient, scalable remote medical guidance, particularly during high-demand situations like COVID-19, though it appears incremental as it applies existing methods to a new domain.
The researchers tackled the problem of medical triage by developing an AI-powered system that uses machine learning and natural language processing on one million teleconsultation records to recommend appropriate care and consultation timing, now certified and in use at Europe's largest telemedicine provider.
Applying state-of-the-art machine learning and natural language processing on approximately one million of teleconsultation records, we developed a triage system, now certified and in use at the largest European telemedicine provider. The system evaluates care alternatives through interactions with patients via a mobile application. Reasoning on an initial set of provided symptoms, the triage application generates AI-powered, personalized questions to better characterize the problem and recommends the most appropriate point of care and time frame for a consultation. The underlying technology was developed to meet the needs for performance, transparency, user acceptance and ease of use, central aspects to the adoption of AI-based decision support systems. Providing such remote guidance at the beginning of the chain of care has significant potential for improving cost efficiency, patient experience and outcomes. Being remote, always available and highly scalable, this service is fundamental in high demand situations, such as the current COVID-19 outbreak.