Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

This review article offers a comprehensive analysis of current developments in the
application of machine learning for cancer diagnostic systems. The effectiveness of machine …

Background As the available information about breast cancer is growing every day, the
decision-making process for the therapy is getting more complex. ChatGPT as a transformer …

Artificial intelligence (AI) and deep learning have emerged as powerful tools in
understanding the etiology and pathogenesis of cancers. These technologies help uncover …

Simple Summary Updated international guidelines suggest NGS as the preferred procedure
for NSCLC patients' evaluation for predictive biomarkers, but NGS facilities are not available …

The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …

Abstract Machine learning (ML) and nanotechnology interfacing are exploring opportunities
for cancer treatment strategies. To improve cancer therapy, this article investigates the …

The impact of polyphenols in ovarian cancer is widely studied observing gene expression,
epigenetic alterations, and molecular mechanisms based on new 'omics' technologies …

In the field of computational oncology, patient status is often assessed using radiology-
genomics, which includes two key technologies and data, such as radiology and genomics …

Aim To systematically identify, describe and evaluate the existing risk prediction models for
cancer‐related fatigue. Design Systematic review. Data Sources Seven databases …