AIMC Topic: Male

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Machine learning and metabolomics identify biomarkers associated with the disease extent of ulcerative colitis.

Journal of Crohn's & colitis Feb 4, 2025
BACKGROUND AND AIMS: Ulcerative colitis (UC) is a metabolism-related chronic intestinal inflammatory disease. Disease extent is a key parameter of UC. Using serum metabolic profiling to identify noninvasive biomarkers of disease extent may inform the...
Biomarkers Female Adult Male Humans Machine Learning Colitis, Ulcerative Discriminant Analysis Middle Aged Severity of Illness Index Case-Control Studies Metabolomics
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Automated Detection of Retinal Detachment Using Deep Learning-Based Segmentation on Ocular Ultrasonography Images.

Translational vision science & technology Feb 3, 2025
PURPOSE: This study aims to develop an automated pipeline to detect retinal detachment from B-scan ocular ultrasonography (USG) images by using deep learning-based segmentation.
Male Middle Aged Deep Learning Ultrasonography Female Humans Aged Adult Image Processing, Computer-Assisted Retinal Detachment
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Retinal Arteriovenous Information Improves the Prediction Accuracy of Deep Learning-Based baPWV Index From Color Fundus Photographs.

Investigative ophthalmology & visual science Feb 3, 2025
PURPOSE: To compare the prediction accuracy of brachial-ankle pulse wave velocity (baPWV) from color fundus photographs (CFPs) using different deep learning models.
Female Aged Adult Male Middle Aged Deep Learning Predictive Value of Tests Blood Pressure Humans Retrospective Studies Photography Retinal Vessels Retinal Artery Pulse Wave Analysis Retinal Vein Fundus Oculi Ankle Brachial Index
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New Method of Early RRMS Diagnosis Using OCT-Assessed Structural Retinal Data and Explainable Artificial Intelligence.

Translational vision science & technology Feb 3, 2025
PURPOSE: The purpose of this study was to provide the development of a method to classify optical coherence tomography (OCT)-assessed retinal data in the context of automatic diagnosis of early-stage multiple sclerosis (MS) with decision explanation.
Nerve Fibers Multiple Sclerosis, Relapsing-Remitting Tomography, Optical Coherence Retina Early Diagnosis Humans Artificial Intelligence Female Young Adult Adult Male Middle Aged Support Vector Machine
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Deep Learning Approaches to Predict Geographic Atrophy Progression Using Three-Dimensional OCT Imaging.

Translational vision science & technology Feb 3, 2025
PURPOSE: To evaluate the performance of various approaches of processing three-dimensional (3D) optical coherence tomography (OCT) images for deep learning models in predicting area and future growth rate of geographic atrophy (GA) lesions caused by ...
Geographic Atrophy Female Aged Male Disease Progression Deep Learning Imaging, Three-Dimensional Tomography, Optical Coherence Macular Degeneration Humans Neural Networks, Computer
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RetOCTNet: Deep Learning-Based Segmentation of OCT Images Following Retinal Ganglion Cell Injury.

Translational vision science & technology Feb 3, 2025
PURPOSE: We present RetOCTNet, a deep learning tool to segment the retinal nerve fiber layer (RNFL) and total retinal thickness automatically from optical coherence tomography (OCT) scans in rats following retinal ganglion cell (RGC) injury.
Animals Male Optic Nerve Injuries Tomography, Optical Coherence Deep Learning Nerve Fibers Rats Retinal Ganglion Cells Disease Models, Animal Ocular Hypertension
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Advanced Artificial-Intelligence-Based Jiang Formula for Intraocular Lens Power in Congenital Ectopia Lentis.

Translational vision science & technology Feb 3, 2025
PURPOSE: The purpose of this study was to develop an artificial intelligence (AI)-based intraocular lens (IOLs) power calculation formula for improving the accuracy of IOLs power calculations in patients with congenital ectopia lentis (CEL).
Visual Acuity Optics and Photonics Lens Implantation, Intraocular Ectopia Lentis Lenses, Intraocular Humans Adolescent Child Artificial Intelligence Young Adult Female Adult Male Refraction, Ocular
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Prospective and External Validation of an Ensemble Learning Approach to Sensitively Detect Intravenous Fluid Contamination in Basic Metabolic Panels.

Clinical chemistry Feb 3, 2025
BACKGROUND: Intravenous (IV) fluid contamination within clinical specimens causes an operational burden on the laboratory when detected, and potential patient harm when undetected. Even mild contamination is often sufficient to meaningfully alter res...
Female Sensitivity and Specificity Male Ensemble Learning Humans Machine Learning Algorithms Prospective Studies
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[Establishing of mortality predictive model for elderly critically ill patients using simple bedside indicators and interpretable machine learning algorithms].

Zhonghua wei zhong bing ji jiu yi xue Feb 1, 2025
OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assess...
Female Aged Humans Male Prognosis Hospital Mortality Machine Learning Retrospective Studies Algorithms APACHE Critical Illness Organ Dysfunction Scores Intensive Care Units
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Prediction of Prostate Cancer Grades Using Radiomic Features.

Acta medica Okayama Feb 1, 2025
We developed a machine learning model for predicting prostate cancer (PCa) grades using radiomic features of magnetic resonance imaging. 112 patients diagnosed with PCa based on prostate biopsy between January 2014 and December 2021 were evaluated. L...
Prostate-Specific Antigen Neoplasm Grading Retrospective Studies Middle Aged Aged Humans Magnetic Resonance Imaging Radiomics Prostatic Neoplasms Machine Learning Male
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