For early detection of cancer tumors, the semantic segmentation based technique is
proposed because the existing numerous methods fail while classifying due to accuracy and …

This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

Precision and timeliness in breast cancer detection are paramount for improving patient
outcomes. Traditional diagnostic methods have predominantly relied on unimodal …

Abstract Background and Objective In Pancreatic Ductal Adenocarcinoma (PDA), multi-omic
models are emerging to answer unmet clinical needs to derive novel quantitative prognostic …

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the
approach to cancer research. Applications of NGS include the identification of tumor specific …

Artificial intelligence algorithms have become extensively utilized in survival analysis for
high-dimensional, multi-source data. However, due to their complexity, these methods often …

The complex pathobiology of lung cancer, and its spread worldwide, has prompted research
studies that combine radiomic and genomic approaches. Indeed, the early identification of …

Breast cancer remains a leading cause of cancer-related mortality among women
worldwide, necessitating early and accurate detection for effective treatment and improved …

Solar photovoltaic (SPV) arrays are crucial components of clean and sustainable energy
infrastructure. However, SPV panels are susceptible to thermal degradation defects that can …

It is imperative that breast cancer is detected precisely and timely to improve patient
outcomes. Diagnostic methodologies have traditionally relied on unimodal approaches; …