However, identifying VETC early remains challenging. Recently, machine learning has shown promise for VETC detection, but their diagnostic accuracy lacks systematic validation. Objective: This ...

Panelists discuss how adherence to guidelines and vigilant imaging support optimal management of CNS disease in EGFR-mutant non–small-cell lung cancer.

This project leverages artificial intelligence to address ethical and privacy concerns in healthcare by generating synthetic brain cancer images. The goal is to create a synthetic dataset that closely ...

Tumor neoantigens possess high specificity and immunogenicity, making them crucial targets for personalized cancer immunotherapies such as mRNA vaccines and T-cell therapies. However, experimental ...

Abstract: Early Detection of brain tumors is essential not only for effective diagnosis but also for improving patient outcomes. This study introduces an automated brain tumor classification system ...

This study explores the feasibility of using breathomic biomarkers analyzed by machine learning as a non-invasive diagnostic tool to differentiate between benign and malignant thoracic lesions, aiming ...