Automated Idiopathic Normal Pressure Hydrocephalus Diagnosis via Artificial Intelligence-Based 3D T1 MRI Volumetric Analysis
AJNR 46:33-40, Lee,J.,et al, 2025
FUTURE-AI: International Consensus Guideline for Trustworthy and Deployable Artificial Intelligence in Healthcare
BMJ 388:e081554, Lekadir,K.,et al, 2025
Calibrating AI Reliance - A Physicians Superhuman Dilemma
JAMA Health Forum 6:e250106, Patil,S.V.,et al, 2025
Validation of an Artificial Intelligence-Powered Virtual Assistant for Emergency Triage in Neurology
Neurologist 30:155-163, Alessandro,L.,et al, 2025
General AI May Revolutionize Neurology 0 Or It Might be Bad
JAMA Neurol doi 10.1001/JAMANEUROL.2025.0905, Westover,M.B. & Westover,A.M., 2025
A Systematic Review and Meta-Analysis of Diagnostic Performance Comparison Between Generative AI and Physicians
NPJ Digital Medicine doi:10.1038/s41746-025-10543, Takita,H.,et al, 2025
Dedicated AI Expert System vs Generative AI with Large Language Model for Clinical Diagnosis
JAMA Network Open 8:e2512994, Feldman,M.J.,et al, 2025
Educational Strategies for Clinical Supervision of Artificial Intelligence Use
NEJM 393:786-797, Abdulnour,R-E. E.,et al, 2025
AI in Neurology: Everything, Everywhere, all at One PRT 2:Speech, Sentience, Scruples, and Service
Ann Neurol 98:431-447, Rizzo, M., 2025
Gait Analysis in Neurologic Disorders, Methodology, Applications and Clinical Considerations
Neurol 105:e214154, Ali,F.,et al, 2025
Neurological Diagnosis, Artificial Intelligence Compared with Diagnostic Generator
Neurologist doi.10.1097/NR.0000000000000560, Finelli,P.F., 2024
Hidden Metastatic Lung Tumour Diagnosed by AI
Lancet 403:1299, Muroya,D.,et al, 2024
Primary Central Nervous System Vasculitis
NEJM 391:1028-1037, Salvarani,C.,et al, 2024
FTC Regulation of AI-Generated Medical Disinformation
JAMA doi:10.1001/JAMA.2024.19971;2024, Haupt,C.E., & Marks,M., 2024
Large Language Models and the Degredation of the Medical Record
NEJM 391:1561-1564, McCoy,L.G.,et al, 2024
How Patients Are Using AI
BMJ 387:q2393, Stokel-Walker,C., 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
Transformation of Undergraduate Medical Education in 2023
JAMA 330:1521-1522, Chang,B.S., 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
Large Language Models in Neurology Research and Future Practice
Neurol 101:1058-1067, Romano,M.F.,et al, 2023
Will Generative Artificial Intelligence Deliver on Its Promise in Health Care?
JAMA doi.10.1001, Nov, Wachter R.M. & Brynjolfsson,E., 2023
Use of GPT-4 to Diagnose Complex Clinical Cases
NEJM AI doi:10.1056/AIp2300031, Eriksen,A.V.,et al, 2023
Study Finds ChatGPT Provides Inaccurate Responses to Drug Questions-Press Release
Am Soc Health Sys Pharm, Dec 5, Grossman,S., 2023
Ethical Considerations in Surgical Decompression for Stroke
Stroke 53:2676-2682, Shlobin, N.A.,et al, 2022
External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke
Ann Neurol 92:943-957, Mair,G.,et al, 2022
Digital Health
Stroke 52:351-355, Silva, G.S. & Schwamm, L.H., 2021
Development and Validation of a Deep Learning-Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images
AJNR 42:838-844, Shin, I.,et al, 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
Machine Learning Approach to Identify Stroke Within 4.5 Hours
Stroke 51:860-866, Lee, H.,et al, 2020
Accuracy of a Machine Learning Muscle MRI - Based Tool for the Diagnosis of Muscular Dystrophies
Neurol 94:e1094-e1102, Verdu-Diaz, J.,et al, 2020
Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs
NEJM 382:1687-1695,1760, Milea, D.,et al, 2020
Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on 18F-Florbetapir PET Using ADNI Data
AJNR 41:980-986, Reith, F.,et al, 2020
Rapid Implementation of Virtual Neurology in Response to the COVID-19 Pandemic
Neurol 94:1077-1087, Grossman, S.N.,et al, 2020
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
Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy
Stroke 48:1416-1419, Labovitz, D.L.,et al, 2017