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Differential
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adverse drug reaction
artificial sweetener
aspartame
attention deficit disorder with hyperactivity
behavior
behavioral disorder
body mass index
cerebrovascular accident
cerebrovascular accident, etiology
cerebrovascular accident, postpartum
cerebrovascular accident, women
coronary artery disease
dementia
diet
electroencephalogram
electroencephalogram, abnormalities of
electroencephalogram, spike activity
gender
headache
hyperactivity
migraine
migraine, foods causing
obesity
Parkinson disease
psychological testing
psychological testing, children
risk factors
saccharin
seizure
seizure, children
seizure, petit mal
small vessel disease
sucralose
sucrose
vascular headache, food causing
Showing articles 0 to 50 of 323 Next >>

Artificially Sweetened Beverages and Stroke, Coronary Heart Disease, and All-Cause Mortality in the Womens Health Initiative
Stroke 50:555-562,549, Mossavar-Rahmani, Y.,et al, 2019

Sugar- and Artificially Sweetened Beverages and the Risks of Incident Stroke and Dementia
Stroke 48:1139-1146, Pase, M.P.,et al, 2017

Aspartame, Behavior, and Cognitive Function in Children with Attention Deficit Disorder
Pediatrics 93:70-75, 127-1281994., Shaywitz,B.A.,et al, 1994

Aspartame Has no Effect on Seizures or Epileptiform Discharged in Epileptic Children
Ann Neurol 35:98-103, Shaywitz,B.A.,et al, 1994

Effects of Diets High in Sucrose or Aspartame on the Behavior and Cognitive Performance of Children
NEJM 330:301-307, 3551994., Wolraich,M.L.,et al, 1994

Aspartame Ingestion and Headaches:A Randomized Crossover Trial
Neurol 44:1787-1793, VanDenEeden,S.K.,et al, 1994

Aspartame Use in Parkinson's Disease
Neurol 43:611-613, Karstaedt,P.J.&Pincus,J.H., 1993

Aspartame Exacerbates EEG Spike-Wave Discharge in Children with Generalized Absence Epilepsy:A Double-Blind Study
Neurol 42:1000-1003, Camfield,P.R.,et al, 1992

Aspartame and Headache
NEJM 318:1200-1202, Lipton,R.B.,et al, 1988

Aspartame & Susceptibility to Headache
NEJM 317:1181-1185, Schiffman,S.S.,et al, 1987

Migraine Provoked by Aspartame
NEJM 314:456, John,D.R., 1986

Neurological Diagnosis, Artificial Intelligence Compared with Diagnostic Generator
Neurologist doi.10.1097/NR.0000000000000560, Finelli,P.F., 2024

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

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

Evaluation of Medical Decision Support Systems (DDX Generators) Using Real Medical Cases of Varying Complexity and Origin
BMC Med Inform Dcis Mak 22:254, Fritz,P.,et al, 2022

Digital Health in Primordial and Primary Stroke Prevention: A Systematic Review
Stroke 53:1008-1019, Feigin, V.L.,et al, 2022

Ethical Considerations in Surgical Decompression for Stroke
Stroke 53:2676-2682, Shlobin, N.A.,et al, 2022

Does Capturing Debris During TAVR Prevent Strokes?
NEJM 387:1318-1319, Carroll, J.D. & Saver, J.L., 2022

Spontaneous Intracerebral Hemorrhage
NEJM 387:1589-1596, Sheth, K.N., 2022

External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke
Ann Neurol 92:943-957, Mair,G.,et al, 2022

Should Electronic Differential Diagnosis Support be Used Early or Late in the Diagnostic Process? A Multicentre Experimental Study of Isabel
BMJ Qual Saf doi:10.1136/bmjqs-2021-013493, Sibbald, M.,et al, 2022

Reaching 95%: Decision Support Tools are the Surest Way to Improve Diagnosis Now
BMJ Qual Saf doi:10.1136/bmjqs-2021-014033, Graber, M.L., 2022

Endovascular Therapy for Acute Stroke with a Large Ischemic Region
NEJM 386:doi.10.1056/NEJMoa2118191, Yoshimura, S.,et al, 2022

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

Assessing the Utility of a Differential Diagnostic Generator in UK General Practice: A Feasibility Study
Diagnosis 8:91-99, Cheraghi-Sohi, S.,et al, 2021

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

Safety and Efficacy of Coma Induction Following First-Line Treatment in Status Epilepticus
Neurol 97:e564-e576, DeStefano, P.,et al, 2021

Artificial Intelligence Applications in Stroke
Stroke 51:2573-2579, Mouridsen, K.,et al, 2020

Tapia Syndrome at the Time of the COVID-19 Pandemic
Neurol 95:312-313, Decavel, P.,et al, 2020

Guillain-Barre Syndrome Associated with SARS-CoV-2
NEJM 382:2574-2576, Tuscano, G.,et al, 2020

Myasthenic Crisis Demanding Mechanical Ventilation
Neurol 94:e299-e313, Neumann, B.,et al, 2020

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

A Young Health Woman with Difficult-to-Wean Acute Ventilator Dependence
Neurol 94:e1340-e1343, Chandrashekhar, S.,et al, 2020

Clinicopathologic Conference, LGI1 autoimmune encephalitis
NEJM 382:1943-1950, Case 15-2020, 2020

Neuropathy, Encephalopathy, Status Epilepticus, and Acute Intermittent Porphyria
Lancet 395:e101, Ahmed, M.A.,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



Showing articles 0 to 50 of 323 Next >>