AIMC Topic: Ophthalmologists

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Robot-assisted tremor control for performance enhancement of retinal microsurgeons.

The British journal of ophthalmology
Pars plana vitrectomy is a challenging, minimally invasive microsurgical procedure due to its intrinsic manoeuvres and physiological limits that constrain human capability. An important human limitation is physiological hand tremor, which can signifi...

Introduction to Machine Learning for Ophthalmologists.

Seminars in ophthalmology
New diagnostic and imaging techniques generate such an incredible amount of data that it is often a challenge to extract all information that could be possibly useful in clinical practice. Machine Learning techniques emerged as an objective tool to a...

Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy.

Ophthalmology
PURPOSE: Use adjudication to quantify errors in diabetic retinopathy (DR) grading based on individual graders and majority decision, and to train an improved automated algorithm for DR grading.

Automated Identification of Diabetic Retinopathy Using Deep Learning.

Ophthalmology
PURPOSE: Diabetic retinopathy (DR) is one of the leading causes of preventable blindness globally. Performing retinal screening examinations on all diabetic patients is an unmet need, and there are many undiagnosed and untreated cases of DR. The obje...

Artificial intelligence versus ophthalmology experts: Comparative analysis of responses to blepharitis patient queries.

European journal of ophthalmology
ObjectiveTo assess the accuracy and clinical education value of responses from AI models (GPT-3.5, GPT-4o, Gemini, Gemini Advanced) compared to expert ophthalmologists' answers to common patient questions about blepharitis, and evaluate their potenti...

Diagnostic report generation for macular diseases by natural language processing algorithms.

The British journal of ophthalmology
AIMS: To investigate rule-based and deep learning (DL)-based methods for the automatically generating natural language diagnostic reports for macular diseases.

Deep learning-based automatic differentiation of acute angle closure with or without zonulopathy using ultrasound biomicroscopy: a comparison of diagnostic performance with ophthalmologists.

BMJ open ophthalmology
OBJECTIVE: This study aims to develop ultrasound biomicroscopy (UBM)-based artificial intelligence (AI) models for preoperative differentiation of acute angle closure (AAC) with or without zonulopathy and to compare their comprehensive diagnostic per...

Evaluation of AI Summaries on Interdisciplinary Understanding of Ophthalmology Notes.

JAMA ophthalmology
IMPORTANCE: Specialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary communication and patient care. The clinical implementation of large language models (LLMs) into pra...

An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.

Translational vision science & technology
PURPOSE: To develop an open-source, fully automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data.