Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective

As health systems organize to deliver the highest quality stroke care to their patients, there is increasing emphasis being placed on prehospital stroke recognition, accurate diagnosis, and efficient triage to improve outcomes after stroke. Emergency medical services (EMS) personnel currently rely heavily on dispatch accuracy, stroke screening tools, bypass protocols and prehospital notification to care for patients with suspected stroke, but novel tools including mobile stroke units and telemedicine-enabled ambulances are already changing the landscape of prehospital stroke care. Herein, the authors provide our perspective on the current state of prehospital stroke diagnosis and triage including several of these emerging trends. Then, we provide commentary to highlight potential artificial intelligence (AI) applications to improve stroke detection, improve accurate and timely dispatch, enhance EMS training and performance, and develop novel stroke diagnostic tools for prehospital use

Global research of artificial intelligence in strabismus: a bibliometric analysis

PurposeTo analyze the global publications on artificial intelligence (AI) in strabismus using a bibliometric approach.MethodsThe Web of Science Core Collection (WoSCC) database was used to retrieve all of the publications on AI in strabismus from 2002 to 2023. We analyzed the publication and citation trend and identified highly-cited articles, prolific countries, institutions, authors and journals, relevant research domains and keywords. VOSviewer (software) and Bibliometrix (package) were used for data analysis and visualization.ResultsBy analyzing a total of 146 relevant publications, this study found an overall increasing trend in the number of annual publications and citations in the last decade. USA was the most productive country with the closest international cooperation. The top 3 research domains were Ophthalmology, Engineering Biomedical and Optics. Journal of AAPOS was the most productive journal in this field. The keywords analysis showed that “deep learning” and “machine learning” may be the hotspots in the future.ConclusionIn recent years, research on the application of AI in strabismus has made remarkable progress. The future trends will be toward optimized technology and algorithms. Our findings help researchers better understand the development of this field and provide valuable clues for future research directions