Improve Robustness of Eye Disease Detection by including Learnable Probabilistic Discrete Latent Variables into Machine Learning Models

arXiv:2402.16865v1 Announce Type: cross
Abstract: Ocular diseases, ranging from diabetic retinopathy to glaucoma, present a significant public health challenge due to their prevalence and potential for causing vision impairment. Early and accurate diagnosis is crucial for effective treatment and management.In recent years, deep learning models have emerged as powerful tools for analysing medical images, including ocular imaging . However, challenges persist in model interpretability and uncertainty estimation, which are critical for clinical decision-making. This study introduces a novel application of …

abstract arxiv challenge cs.cv cs.lg detection diagnosis disease diseases eess.iv health machine machine learning machine learning models management public public health robustness treatment type variables vision