AI-based Advanced approaches and dry eye disease detection based on multi-source evidence: Cases, applications, issues, and future directions
This study explores the potential of Artificial Intelligence (AI) in early screening and
prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic …
prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic …
AI-based methods for detecting and classifying age-related macular degeneration: a comprehensive review
This paper explores the advancements and achievements of artificial intelligence (AI) in
computer vision (CV), particularly in the context of diagnosing and grading age-related …
computer vision (CV), particularly in the context of diagnosing and grading age-related …
[HTML][HTML] A Method for Ocular Disease Diagnosis through Visual Prediction Explainability
Ocular diseases can range in severity, with some being more serious than others. As a
matter of fact, there are several common and severe eye diseases, for instance, glaucoma …
matter of fact, there are several common and severe eye diseases, for instance, glaucoma …
Can Explainable Artificial Intelligence Optimize the Data Quality of Machine Learning Model? Taking Meibomian Gland Dysfunction Detections as a Case Study
MH Wang, R Zhou, Z Lin, Y Yu, P Zeng… - Journal of Physics …, 2023 - iopscience.iop.org
Data quality plays a crucial role in computer-aided diagnosis (CAD) for ophthalmic disease
detection. Various methodologies for data enhancement and preprocessing exist, with …
detection. Various methodologies for data enhancement and preprocessing exist, with …
Applications of Explainable Artificial Intelligent Algorithms to Age-related Macular Degeneration Diagnosis: A Case Study Based on CNN, Attention, and CAM …
The recent years have witnessed extensive research on Explainable Artificial Intelligence
(XAI) algorithms in the field of ophthalmology. This paper introduces an improved deep …
(XAI) algorithms in the field of ophthalmology. This paper introduces an improved deep …
Developing a transparent diagnosis model for diabetic retinopathy using explainable AI
Diabetic retinopathy is a leading cause of vision complications and partially sighted which
pose considerable diagnostic difficulties because of its diverse and varying symptoms …
pose considerable diagnostic difficulties because of its diverse and varying symptoms …
Artificial Intelligence in Retinal Screening Using OCT Images: A Review of the Last Decade (2013-2023)
Background and objectives Optical coherence tomography (OCT) has ushered in a
transformative era in the domain of ophthalmology, offering non-invasive imaging with high …
transformative era in the domain of ophthalmology, offering non-invasive imaging with high …
[HTML][HTML] Recent Applications of Explainable AI (XAI): A Systematic Literature Review
M Saarela, V Podgorelec - Applied Sciences, 2024 - mdpi.com
This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
[HTML][HTML] Smart Vision Transparency: Efficient Ocular Disease Prediction Model Using Explainable Artificial Intelligence
The early prediction of ocular disease is certainly an obligatory concern in the domain of
ophthalmic medicine. Although modern scientific discoveries have shown the potential to …
ophthalmic medicine. Although modern scientific discoveries have shown the potential to …
Optimizing Real-Time Trichiasis Object Detection: A Comparative Analysis of YOLOv5 and YOLOv8 Performance Metrics
This study evaluates and compares the performance of YOLOv5 and YOLOv8 in trichiasis
object detection tasks, focusing on key metrics such as mean Average Precision (mAP) …
object detection tasks, focusing on key metrics such as mean Average Precision (mAP) …