A systematic literature review on diabetic retinopathy using an artificial intelligence approach
Diabetic retinopathy occurs due to long-term diabetes with changing blood glucose levels
and has become the most common cause of vision loss worldwide. It has become a severe …
and has become the most common cause of vision loss worldwide. It has become a severe …
Joint self-supervised image-volume representation learning with intra-inter contrastive clustering
Collecting large-scale medical datasets with fully annotated samples for training of deep
networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs in …
networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs in …
Prompt-driven latent domain generalization for medical image classification
Deep learning models for medical image analysis easily suffer from distribution shifts
caused by dataset artifact bias, camera variations, differences in the imaging station, etc …
caused by dataset artifact bias, camera variations, differences in the imaging station, etc …
A review of machine learning in scanpath analysis for passive gaze-based interaction
The scanpath is an important concept in eye tracking. It refers to a person's eye movements
over a period of time, commonly represented as a series of alternating fixations and …
over a period of time, commonly represented as a series of alternating fixations and …
Drg-net: interactive joint learning of multi-lesion segmentation and classification for diabetic retinopathy grading
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world, and early DR
detection is necessary to prevent vision loss and support an appropriate treatment. In this …
detection is necessary to prevent vision loss and support an appropriate treatment. In this …
Combining datasets to improve model fitting
For many use cases, combining information from different datasets can be of interest to
improve a machine learning model's performance, especially when the number of samples …
improve a machine learning model's performance, especially when the number of samples …
YOLO for Lung Disease Detection from CT Scans
M Mousavi, FS Mirshafiee, E Shahbazi… - 2023 IEEE 21st …, 2023 - ieeexplore.ieee.org
Detection and localization of current lung diseases in computer tomography (CT) scans is
challenging due to the complexity of the task and similarity between neighboring slices …
challenging due to the complexity of the task and similarity between neighboring slices …
Domain Adaptive Diabetic Retinopathy Grading with Model Absence and Flowing Data
Domain shift (the difference between source and target domains) poses a significant
challenge in clinical applications, eg, Diabetic Retinopathy (DR) grading. Despite …
challenge in clinical applications, eg, Diabetic Retinopathy (DR) grading. Despite …