The emergence of digital pathology—an image-based environment for the acquisition,
management and interpretation of pathology information supported by computational …

Objectives In this systematic review we aimed at assessing how artificial intelligence (AI),
including machine learning (ML) techniques have been deployed to predict, diagnose, and …

The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

The application of deep learning for automated segmentation (delineation of boundaries) of
histologic primitives (structures) from whole slide images can facilitate the establishment of …

Background Nephropathologic analyses provide important outcomes-related data in
experiments with the animal models that are essential for understanding kidney disease …

Abstract Background and Objective: Glomeruli identification, ie, detection and
characterization, is a key procedure in many nephropathology studies. In this paper …

To improve the diagnosis of Lupus Nephritis (LN), a multilevel LN image segmentation
method is developed in this paper based on an improved slime mould algorithm. The search …

Assessment of renal function and structure accurately remains essential in the diagnosis
and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic …

Malaria refers to a contagious mosquito-borne disease caused by parasite genus
plasmodium transmitted by mosquito female Anopheles. As infected mosquito bites a …

Background Automated classification of glomerular pathological findings is potentially
beneficial in establishing an efficient and objective diagnosis in renal pathology. While …