This paper explores the application of deep learning techniques for the automated analysis
of histopathology images, with a focus on cancer diagnosis. Histopathology images play a …

Explainable Artificial Intelligence (XAI) has emerged as a critical area of research,
particularly in the medical domain, where the decisions made by AI systems can have a …

Federated learning is a distributed machine learning approach that enables model training
across multiple decentralized edge devices or servers holding local data samples without …

Cancer, a complex and heterogeneous disease, presents a significant challenge in
healthcare. Traditional treatment approaches often rely on a" one-size-fits-all" methodology …

In 2024, the threat landscape for organizations has evolved significantly, with malware
remaininga predominant and ever-growing concern. This paper examines the rising tide of …

This research paper explores the crucial role of human-centric design in the development of
AI-driven clinical decision support systems (CDSS). By focusing on user-centered design …

Predictive maintenance is a critical aspect of ensuring the reliability and availability of
medical equipment in healthcare facilities. Machine learning (ML) algorithms have emerged …

This paper explores the implementation of AI-driven solutions for Clinical Documentation
Improvement (CDI) in Electronic Health Records (EHRs). The aim is to enhance the …

The process of drug discovery and development is time-consuming, expensive, and often
fails to yield new therapeutic options. Drug repurposing, the identification of new therapeutic …

Explainable Artificial Intelligence (XAI) has emerged as a critical area of research to
enhance the transparency and interpretability of complex machine learning models …