AI Medical Compendium Topic

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Eyelids

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Differentiating malignant and benign eyelid lesions using deep learning.

Scientific reports
Artificial intelligence as a screening tool for eyelid lesions will be helpful for early diagnosis of eyelid malignancies and proper decision-making. This study aimed to evaluate the performance of a deep learning model in differentiating eyelid lesi...

A framework for generalizable neural networks for robust estimation of eyelids and pupils.

Behavior research methods
Deep neural networks (DNNs) have enabled recent advances in the accuracy and robustness of video-oculography. However, to make robust predictions, most DNN models require extensive and diverse training data, which is costly to collect and label. In t...

Diagnosing lagophthalmos using artificial intelligence.

Scientific reports
Lagophthalmos is the incomplete closure of the eyelids posing the risk of corneal ulceration and blindness. Lagophthalmos is a common symptom of various pathologies. We aimed to program a convolutional neural network to automatize lagophthalmos diagn...

Artificial intelligence to automate assessment of ocular and periocular measurements.

European journal of ophthalmology
PURPOSE: To develop and validate a deep learning facial landmark detection network to automate the assessment of periocular anthropometric measurements.

Artificial intelligence-assisted grading for tear trough deformity.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Various classification systems for tear trough deformity (TTD) have been published; however, their complexity can pose challenges in clinical use, especially for less experienced surgeons. It is believed that artificial intelligence (AI) ...

Computer-aided diagnosis of eyelid skin tumors using machine learning.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To develop an automated, new framework based on machine learning to diagnose malignant eyelid skin tumors.

Computer Vision Identification of Trachomatous Inflammation-Follicular Using Deep Learning.

Cornea
PURPOSE: Trachoma surveys are used to estimate the prevalence of trachomatous inflammation-follicular (TF) to guide mass antibiotic distribution. These surveys currently rely on human graders, introducing a significant resource burden and potential f...

Dynamic blinking feature extraction for automated facial nerve paralysis detection.

Computers in biology and medicine
Facial nerve paralysis (FNP) impair eyelid closure and blinking, risking ophthalmic complications and vision loss. Current detection methods primarily rely on static facial asymmetries, overlooking the dynamic eyelid movements during blinking that ar...

Deep learning based adaptive and automatic measurement of palpebral margin in eyelid morphology.

Scientific reports
Accurate anatomical measurements of the eyelids are essential in periorbital plastic surgery for both disease treatment and procedural planning. Recent researches in eye diseases have adopted deep learning works to measure MRD. However, such works en...