A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

Novel Graph Neural Network (N-GNN) Model Achieves Superior Accuracy in Early Lung Cancer Detection, Paving the Way for Enhanced Diagnostic Capabilities. The research, a collaboration between BioMark's ...

Electronic nose breath analysis achieved 80-92% accuracy for detecting lung cancer in patients with suspicious findings. Detection accuracy remained consistent across tumor characteristics, disease ...

Please provide your email address to receive an email when new articles are posted on . Machine learning models can predict which patients receiving lung cancer therapy may need urgent care visits.

Using Natural Language Processing to Assess Goals-of-Care Conversations for Patients With Cancer We combined natural language processing and large language models with state-of-the-art machine ...

Cancer diagnoses traditionally require invasive or labor-intensive procedures such as tissue biopsies. Researchers at the Ludwig-Maximilians-Universität München (LMU) have now reported on a method ...