Search Results for author:
Found 6 papers, 1 papers with code
A Comprehensive Review of Artificial Intelligence Applications in Major Retinal Conditions
This paper provides a systematic survey of retinal diseases that cause visual impairments or blindness, emphasizing the importance of early detection for effective treatment.
Identifying factors associated with fast visual field progression in patients with ocular hypertension based on unsupervised machine learning
We characterized the subtypes based on demographic, clinical, ocular, and VF factors at the baseline.
ChatGPT Assisting Diagnosis of Neuro-ophthalmology Diseases Based on Case Reports
With further development, ChatGPT Plus v4. 0 may have potential to be used in clinical care settings to assist clinicians in providing quick, accurate diagnoses of patients in neuro-ophthalmology.
Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification
We extend Maximum Mean Discrepancy (MMD), Low-rank coding, and Correlation Alignment (CORAL) to compute the adaptation loss in three base models.
Artificial Intelligence Models for Cell Type and Subtype Identification Based on Single-Cell RNA Sequencing Data in Vision Science
Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within heterogeneous cell populations from various tissues.
A Survey of Human Activity Recognition Using WiFi CSI
This is done by extracting features from CSI data streams and using machine learning techniques to build models and classifiers.
