Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …

Artificial Intelligence (AI) has transformed how we live and how we think, and it will change
how we practice medicine. With multimodal big data, we can develop large medical models …

This paper focuses on the use of local Explainable Artificial Intelligence (XAI) methods,
particularly the Local Rule-Based Explanations (LORE) technique, within healthcare and …

Deep learning integration in cancer diagnosis enhances accuracy and diagnosis speed
which helps clinical decision-making and improves health outcomes. Despite all these …

Background Multiparametric MRI can help identify clinically significant prostate cancer
(csPCa)(Gleason score≥ 7) but is limited by reader experience and interobserver variability …

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection
compared with systematic biopsy, but its interpretation is prone to interreader variation …

Cancer remains a leading reason of mortality, with the current global death toll estimated at
10 million and projected to surpass 16 million by 2040 as reported by the World Health …

Objectives To develop and test zone-specific prostate-specific antigen density (sPSAD)
combined with PI-RADS to guide prostate biopsy decision strategies (BDS). Methods This …

Artificial Intelligence (AI) plays an increasingly integral role in decision-making processes. In
order to foster trust in AI predictions, many approaches towards explainable AI (XAI) have …