This article delves into the critical integration of domain knowledge into AI/ML systems
across various industries, highlighting its importance in develo** ethically responsible …

While deep learning has shown promise in improving the automated diagnosis of disease
based on chest X-rays, deep networks may exhibit undesirable behavior related to short …

A cyber–cyber digital twin is a simulation of a software system. By contrast, a cyber–physical
digital twin is a simulation of a non-software (physical) system. Although cyber–physical …

Computer-aided breast mass classification is an effective and widely used technology to
assist pathologists in formulating clinical diagnoses and improving working efficiencies …

Background: Development of deep convolutional neural networks for breast cancer
classification has taken significant steps towards clinical adoption. It is though unclear how …

Radiologists consider fine-grained characteristics of mammograms as well as patient-
specific information before making the final diagnosis. Recent literature suggests that a …

Machine learning and deep learning methods have become essential for computer-assisted
prediction in medicine, with a growing number of applications also in the field of …

Over the past decades, the incidence of thyroid cancer has been increasing globally.
Accurate and early diagnosis allows timely treatment and helps to avoid over-diagnosis …

Most deep learning models in chest X-ray prediction utilize the posteroanterior (PA) view
due to the lack of other views available. PadChest is a large-scale chest X-ray dataset that …

Traditionally, deep learning methods for breast cancer classification perform a single-view
analysis. However, radiologists simultaneously analyze all four views that compose a …