AIMC Topic: Neurologists

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Deep Learning Versus Neurologists: Functional Outcome Prediction in LVO Stroke Patients Undergoing Mechanical Thrombectomy.

Stroke Jun 14, 2023
BACKGROUND: Despite evolving treatments, functional recovery in patients with large vessel occlusion stroke remains variable and outcome prediction challenging. Can we improve estimation of functional outcome with interpretable deep learning models u...
Thrombectomy Neurologists Stroke Brain Ischemia Prognosis Humans Retrospective Studies Treatment Outcome Ischemic Stroke Deep Learning
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Review of Machine Learning and Artificial Intelligence (ML/AI) for the Pediatric Neurologist.

Pediatric neurology Jan 13, 2023
Artificial intelligence (AI) and a popular branch of AI known as machine learning (ML) are increasingly being utilized in medicine and to inform medical research. This review provides an overview of AI and ML (AI/ML), including definitions of common ...
Humans Artificial Intelligence Machine Learning Neurologists Infant, Newborn Child
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Assistance from Automated ASPECTS Software Improves Reader Performance.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association May 11, 2021
PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with...
Automation Middle Cerebral Artery Radiographic Image Interpretation, Computer-Assisted Observer Variation Carotid Artery, Internal Neurologists Clinical Competence Magnetic Resonance Imaging Ischemic Stroke Radiologists Predictive Value of Tests Male Middle Aged Reproducibility of Results Machine Learning Aged Software Tomography, X-Ray Computed Female Prognosis Humans
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Evaluation of artificial intelligence systems for assisting neurologists with fast and accurate annotations of scalp electroencephalography data.

EBioMedicine Mar 18, 2021
BACKGROUND: Assistive automatic seizure detection can empower human annotators to shorten patient monitoring data review times. We present a proof-of-concept for a seizure detection system that is sensitive, automated, patient-specific, and tunable t...
Data Analysis Algorithms Reproducibility of Results Deep Learning Brain Seizures Humans Neurologists Artificial Intelligence Electroencephalography Epilepsy
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Deep Learning-Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model.

JAMA network open Jun 5, 2019
IMPORTANCE: Deep learning has the potential to augment clinician performance in medical imaging interpretation and reduce time to diagnosis through automated segmentation. Few studies to date have explored this topic.
Neurologic Examination Male Middle Aged Neurologists Retrospective Studies Humans Clinical Competence Diagnosis, Computer-Assisted Cross-Over Studies Female Deep Learning Intracranial Aneurysm Computer Simulation
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Machine learning in neurology: what neurologists can learn from machines and vice versa.

Journal of neurology Aug 2, 2018
Artificial intelligence is increasingly becoming a part of everyday life. This raises the question whether clinical neurology can benefit from these novel methods to increase diagnostic accuracy. Several recent studies have used machine learning clas...
Nervous System Diseases Learning Neurologists Humans Neurology Diagnosis, Computer-Assisted Machine Learning
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Neurologists and Clinical Informatics: Realizing the Potential of Digital Medicine.

Seminars in neurology Aug 1, 2025
Clinical informatics (CI) is an emerging field within biomedical informatics that sits at the intersection of clinical care, health systems, and health information technology (IT). CI emphasizes how individuals (neurologists, patients, staff) interac...
Humans Medical Informatics Neurology Neurologists Artificial Intelligence Electronic Health Records
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