External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke
Ann Neurol 92:943-957, Mair,G.,et al, 2022
Artificial Intelligence Applications in Stroke
Stroke 51:2573-2579, Mouridsen, K.,et al, 2020
Automated ASPECTS in Acute Ischmeic Stroke: A Comparative Analysis with CT Perfusion
AJNR 40:2033-2038, Sundaram, V.K.,et al, 2019
Neurological Diagnosis, Artificial Intelligence Compared with Diagnostic Generator
Neurologist doi.10.1097/NR.0000000000000560, Finelli,P.F., 2024
Artificial Intelligence and Machine Learning in Clinical Medicine, 2023
NEjM 388:1201-1208,1220, Haug,C.H. & Drazen,J.M., 2023
Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine
NEJM 388:1233-1239, Lee,P., et al, 2023
The New Era of Automated Electroencephalogram Interpretation
JAMA Neurol 80:777-778, Kleen,J.K., & Guterman,E.L., 2023
Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge
JAMA 330:78-79, Kanjee,Z.,et al, 2023
Improving Neurology Clinical Care with Natural Language Processing Tools
Neurol 101:1010-1018, Ge,W.,et al, 2023
Use of GPT-4 to Diagnose Complex Clinical Cases
NEJM AI doi:10.1056/AIp2300031, Eriksen,A.V.,et al, 2023
Ethical Considerations in Surgical Decompression for Stroke
Stroke 53:2676-2682, Shlobin, N.A.,et al, 2022
Digital Health
Stroke 52:351-355, Silva, G.S. & Schwamm, L.H., 2021
The First Examination of Diagnostic Performance of Automated Measurement of the Callosal Angle in 1856 Elderly Patients and Volunteers Indicates that 12.4% of Exams Met the Criteria for Possible Normal Pressure Hydrocephalus
AJNR 42:1942-1948, Morzage, M.,et al, 2021
Next-Generation Artificial Intelligence for Diagnosis
JAMA doi:10.1001/JAMA/2021.22396, Dec, Adler-Milstein, J.,et al, 2021
Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs
NEJM 382:1687-1695,1760, Milea, D.,et al, 2020
Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy
Stroke 48:1416-1419, Labovitz, D.L.,et al, 2017