Additionally, the detection of methylation patterns in circulating tumor DNA using next-generation sequencing methods could be used to non-invasively screen for lung cancer.

In the former scenario, the deep learning algorithm—which was trained on computed tomography scans of people with lung cancer, without it, and with nodules turned cancerous, the New York Times ...

Woese Institute for Genomic Biology are a step closer to realizing this goal by integrating machine learning-based analysis into point-of-care biosensing technologies. The new method, ...

A Michigan Tech-developed machine learning model uses probability to more accurately classify breast cancer shown in histopathology images and evaluate the uncertainty of its predictions.

Lung cancer is the leading cause of cancer deaths worldwide. Screening is key for early detection and increased survival, but the current method has a 96 percent false positive rate. Using machine ...

Researchers say findings provide compelling evidence underscoring the potential of electric-field molecular fingerprinting for minimally invasive disease detection.

Early candidate nasal swab classifiers developed using machine learning and whole transcriptome sequencing may improve early lung cancer detection.