AIMC Topic: Cross-Sectional Studies

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Hypomagnesemia and 25-hydroxyvitamin D deficiency in patients with long COVID.

Magnesium research
Clinical manifestations related to hypomagnesemia and/or deficiency of vitamin D are frequent in patients with an extended course of coronavirus disease-2019 (long COVID). To evaluate hypomagnesemia and hydroxyvitamin D deficiency in patients with lo...

[Application of Deep Learning Algorithm in the Grading Assessment of Corneal Fluorescein Staining].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To explore the application value of applying deep learning (DL) algorithm in the grading assessment of corneal fluorescein staining.

Using Artificial Intelligence to Identify the Associations of Children's Performance of Coloring, Origami, and Copying Activities With Visual-Motor Integration.

The American journal of occupational therapy : official publication of the American Occupational Therapy Association
IMPORTANCE: Performance of coloring, origami, and copying activities reflects children's visual-motor integration (VMI), but the levels of association remain unclear.

Evaluation and Comparison of Ophthalmic Scientific Abstracts and References by Current Artificial Intelligence Chatbots.

JAMA ophthalmology
IMPORTANCE: Language-learning model-based artificial intelligence (AI) chatbots are growing in popularity and have significant implications for both patient education and academia. Drawbacks of using AI chatbots in generating scientific abstracts and...

Validation of an artificial intelligence-based method to automate Cobb angle measurement on spinal radiographs of children with adolescent idiopathic scoliosis.

European journal of physical and rehabilitation medicine
BACKGROUND: Accurately measuring the Cobb angle on radiographs is crucial for diagnosis and treatment decisions for adolescent idiopathic scoliosis (AIS). However, manual Cobb angle measurement is time-consuming and subject to measurement variation, ...

Geographic Atrophy Segmentation Using Multimodal Deep Learning.

Translational vision science & technology
PURPOSE: To examine deep learning (DL)-based methods for accurate segmentation of geographic atrophy (GA) lesions using fundus autofluorescence (FAF) and near-infrared (NIR) images.

Deep Learning Algorithm Detects Presence of Disorganization of Retinal Inner Layers (DRIL)-An Early Imaging Biomarker in Diabetic Retinopathy.

Translational vision science & technology
PURPOSE: To develop and train a deep learning-based algorithm for detecting disorganization of retinal inner layers (DRIL) on optical coherence tomography (OCT) to screen a cohort of patients with diabetic retinopathy (DR).

Fundus Tessellated Density Assessed by Deep Learning in Primary School Children.

Translational vision science & technology
PURPOSE: To explore associations of fundus tessellated density (FTD) and compare characteristics of different fundus tessellation (FT) distribution patterns, based on artificial intelligence technology using deep learning.

Performance of an Artificial Intelligence Chatbot in Ophthalmic Knowledge Assessment.

JAMA ophthalmology
IMPORTANCE: ChatGPT is an artificial intelligence (AI) chatbot that has significant societal implications. Training curricula using AI are being developed in medicine, and the performance of chatbots in ophthalmology has not been characterized.

Estimation of Visual Function Using Deep Learning From Ultra-Widefield Fundus Images of Eyes With Retinitis Pigmentosa.

JAMA ophthalmology
IMPORTANCE: There is no widespread effective treatment to halt the progression of retinitis pigmentosa. Consequently, adequate assessment and estimation of residual visual function are important clinically.