AIMC Topic: Dilatation, Pathologic
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Validation of an Artificial Intelligence-based Tool - The Screening Corneal Objective Risk of Ectasia Integrated into Anterion for Detection of Corneal Ectasia/Risk of Ectasia.
Middle East African journal of ophthalmology
Dec 2, 2024
PURPOSE: The purpose of this study was to validate the artificial intelligence-based Screening Corneal Objective Risk of Ectasia (SCORE) for the detection of corneal ectasia/risk of ectasia and to find the mean SCORE value in normal eyes.
High-level feature-guided attention optimized neural network for neonatal lateral ventricular dilatation prediction.
Medical physics
Aug 27, 2024
BACKGROUND: Periventricular-intraventricular hemorrhage can lead to posthemorrhagic ventricular dilatation or even posthemorrhagic hydrocephalus if not detected promptly. Sequential cranial ultrasound scans are typically used for their diagnoses. Non...
Application of an artificial intelligence ensemble for detection of important secondary findings on lung ventilation and perfusion SPECT-CT.
Clinical imaging
May 2, 2023
RATIONALE: Single-photon-emission-computerized-tomography/computed-tomography(SPECT/CT) is commonly used for pulmonary disease. Scant work has been done to determine ability of AI for secondary findings using low-dose-CT(LDCT) attenuation correction ...
Detection of intracranial aneurysms using deep learning-based CAD system: usefulness of the scores of CNN's final layer for distinguishing between aneurysm and infundibular dilatation.
Japanese journal of radiology
Sep 29, 2022
PURPOSE: We evaluated the diagnostic performance of a clinically available deep learning-based computer-assisted diagnosis software for detecting unruptured aneurysms (UANs) using magnetic resonance angiography and assessed the functionality of the c...
Prediction of Distal Aortic Enlargement after Proximal Repair of Aortic Dissection Using Machine Learning.
Annals of vascular surgery
Apr 3, 2021
OBJECTIVES: This study aimed to construct a risk prediction model for distal aortic enlargement in patients with type B aortic dissection (TBAD) treated with proximal thoracic endovascular aortic repair (TEVAR).
Neural Networks, Computer
Decision Support Techniques
Retrospective Studies
Electronic Health Records
Humans
Adult
Dilatation, Pathologic
Male
Middle Aged
Risk Assessment
Clinical Decision-Making
Female
Risk Factors
Aged
Aortic Aneurysm, Thoracic
Aorta
Blood Vessel Prosthesis Implantation
Time Factors
Aortic Rupture
Endovascular Procedures
Treatment Outcome
Vascular Remodeling
Support Vector Machine
Aortic Dissection
Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.
American journal of ophthalmology
Feb 9, 2021
PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL];...
Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants.
Scientific reports
Jan 12, 2021
To train, evaluate, and validate the application of a deep learning framework in three-dimensional ultrasound (3D US) for the automatic segmentation of ventricular volume in preterm infants with post haemorrhagic ventricular dilatation (PHVD). We tra...
The Role of Corneal Biomechanics for the Evaluation of Ectasia Patients.
International journal of environmental research and public health
Mar 23, 2020
PURPOSE: To review the role of corneal biomechanics for the clinical evaluation of patients with ectatic corneal diseases.
Artificial intelligence using a convolutional neural network for automatic detection of small-bowel angioectasia in capsule endoscopy images.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Oct 2, 2019
BACKGROUND AND AIM: Although small-bowel angioectasia is reported as the most common cause of bleeding in patients and frequently diagnosed by capsule endoscopy (CE) in patients with obscure gastrointestinal bleeding, a computer-aided detection metho...
Keratoconus severity identification using unsupervised machine learning.
PloS one
Nov 6, 2018
We developed an unsupervised machine learning algorithm and applied it to big corneal parameters to identify and monitor keratoconus stages. A big dataset of corneal swept source optical coherence tomography (OCT) images of 12,242 eyes acquired from ...
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