Cancer Diagnostics – News and Features

New results indicate that AI-supported breast screening can detect 29% more cancer cases than traditional screening.

A study from Moffitt Cancer Center and the University of Michigan shows that AI-assisted radiotherapy can help doctors make more consistent treatment decisions for lung and liver cancer. However, doctors' trust in AI recommendations varies.

A study finds that celecoxib improves disease-free survival in stage 3 colon cancer patients with positive ctDNA after surgery. The analysis highlights ctDNA’s predictive role in identifying patients who may benefit from anti-inflammatory drugs.

In this article, Momin Shah discusses how to ensure that NGS protocols are optimized from the outset to save time and costs on new research projects.

Functional genomics can help deconvolute the link between genotype and phenotype in disease, revealing new drug targets and progressing understanding of existing drugs.

Successful test in breast cancer patients: the active agent digoxin, a cardiac medication, dissolves clusters of circulating breast cancer cells in the blood, thus reducing the risk of metastases formation.

A new machine learning-powered blood test can detect multiple types of cancer in their earliest stages.

A study finds that a sensitive test detecting circulating tumour DNA (ctDNA) in early-stage lung cancer can predict relapse risk and survival. This approach could help doctors personalize treatment and improve patient outcomes.

A study has demonstrated that biomarker testing in smokers and ex-smokers can reduce lung cancer deaths by 40%. This large-scale trial highlights how measurable biological indicators enable earlier detection of lung cancer, improving survival rates.

University of Michigan researchers developed a biolaser-based method to detect circulating tumor cells in pancreatic and lung cancer patients. By combining cell lasers with machine learning, the technique identifies tumor cells with 99% accuracy.