AIMC Topic: Arnold-Chiari Malformation

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Phase-contrast magnetic resonance imaging-based predictive modelling for surgical outcomes in patients with Chiari malformation type 1 with syringomyelia: a machine learning study.

Clinical radiology Jan 29, 2025
AIM: Prospective outcome prediction plays a crucial role in guiding preoperative decision-making in patients with Chiari malformation type I (CM-Ⅰ) with syringomyelia. Here, we aimed to develop a predictive model for postoperative outcomes in patient...
Retrospective Studies Female Young Adult Humans Machine Learning Predictive Value of Tests Decompression, Surgical Arnold-Chiari Malformation Syringomyelia Middle Aged Treatment Outcome Magnetic Resonance Imaging Adult Male
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Artificial intelligence versus clinical judgement: how accurately do generative models reflect CNS guidelines for chiari malformation?

Clinical neurology and neurosurgery Nov 26, 2024
OBJECTIVE: This study investigated the response and readability of generative artificial intelligence (AI) models to questions and recommendations proposed by the 2023 Congress of Neurological Surgeons (CNS) guidelines for Chiari 1 malformation.
Practice Guidelines as Topic Humans Arnold-Chiari Malformation Artificial Intelligence Clinical Reasoning
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Using Artificial Intelligence to Identify Three Presenting Phenotypes of Chiari Type-1 Malformation and Syringomyelia.

Neurosurgery Nov 18, 2024
BACKGROUND AND OBJECTIVES: Chiari type-1 malformation (CM1) and syringomyelia (SM) are common related pediatric neurosurgical conditions with heterogeneous clinical and radiological presentations that offer challenges related to diagnosis and managem...
Male Infant Adolescent Phenotype Humans Female Artificial Intelligence Adult Registries Arnold-Chiari Malformation Syringomyelia Cohort Studies Child, Preschool Child
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Harnessing artificial intelligence to improve surgical precision in Chiari malformation.

Neurosurgical review Sep 19, 2024
Humans Artificial Intelligence Neurosurgical Procedures Arnold-Chiari Malformation
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Machine learning for enhanced prognostication: predicting 30-day outcomes following posterior fossa decompression surgery for Chiari malformation type I in a pediatric cohort.

Journal of neurosurgery. Pediatrics Apr 12, 2024
OBJECTIVE: Chiari malformation type I (CM-I) is a congenital disorder occurring in 0.1% of the population. In symptomatic cases, surgery with posterior fossa decompression (PFD) is the treatment of choice. Surgery is, however, associated with peri- a...
Arnold-Chiari Malformation Cranial Fossa, Posterior Child, Preschool Child Treatment Outcome Patient Readmission Reoperation Decompression, Surgical Postoperative Complications Adolescent Cohort Studies Female Male Humans Machine Learning Prognosis Retrospective Studies
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Use of deep learning in the MRI diagnosis of Chiari malformation type I.

Neuroradiology Feb 24, 2022
PURPOSE: To train deep learning convolutional neural network (CNN) models for classification of clinically significant Chiari malformation type I (CM1) on MRI to assist clinicians in diagnosis and decision making.
Humans Magnetic Resonance Imaging Arnold-Chiari Malformation Neural Networks, Computer Retrospective Studies Female Adult Deep Learning
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Using machine learning to understand neuromorphological change and image-based biomarker identification in Cavalier King Charles Spaniels with Chiari-like malformation-associated pain and syringomyelia.

Journal of veterinary internal medicine Sep 24, 2019
BACKGROUND: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and secondary syringomyelia (SM). Chiari-like malformation-associated pain (CM-P) can be challenging to d...
Dogs Dog Diseases Pain Arnold-Chiari Malformation Syringomyelia Male ROC Curve Area Under Curve Sensitivity and Specificity Animals Biomarkers Retrospective Studies Female Machine Learning
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Machine learning applied to neuroimaging for diagnosis of adult classic Chiari malformation: role of the basion as a key morphometric indicator.

Journal of neurosurgery Oct 20, 2017
OBJECTIVE The current diagnostic criterion for Chiari malformation Type I (CM-I), based on tonsillar herniation (TH), includes a diversity of patients with amygdalar descent that may be caused by a variety of factors. In contrast, patients presenting...
Arnold-Chiari Malformation Humans Encephalocele Skull Base Machine Learning Foramen Magnum Logistic Models Amygdala Adult Cephalometry Decision Trees Neuroimaging Diagnosis, Differential
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