Abstract Machine learning and artificial intelligence approaches have revolutionized
multiple disciplines, including toxicology. This review summarizes representative recent …

In recent years, various AI-based methods have been developed in order to uncover
chemico-biological interactions associated with DNA damage and oxidative stress. Various …

Background and Objective: DNA damage analysis can provide valuable information in
several areas ranging from the diagnosis/treatment of a disease to the monitoring of the …

Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative
computational method for the assessment of textural patterns, applicable in almost any area …

Comet assay is a widely used technique to assess and quantify DNA damage in individual
cells. Recently, researchers have applied various deep learning techniques to automate the …

Employees are one of the most important resources of a company. The churn of valuable
employees significantly affects a company's performance. The design of systems that predict …

Abstract Convolutional Neural Networks (CNNs) are the most important deep learning
algorithms to classify images based on their visual features. CNNs architectures are made of …

Comet assay is a widely used method, especially in the field of genotoxicity, to quantify and
measure DNA damage visually at the level of individual cells with high sensitivity and …

DNA damage is a common cellular feature seen in cancer and neurodegenerative disease,
but fast and accurate methods for quantifying DNA damage are lacking. Comet assays are a …

Medical image segmentation is a crucial step in developing computer-Aided Diagnosis
(CAD), which supports the physician to adopt a suitable procedure about the clinical case …