Esophageal squamous cell carcinoma (ESCC) is a severe health threat, being a predominant subtype of esophageal cancer and ...

AI based models achieved an accuracy rate of 86% for detecting ovarian cancer, compared to 82% for human experts.

Determining which cancer patients are a good candidate for immune checkpoint inhibitors can be a challenge, but researchers at Mount Sinai and Memorial Sloan Kettering Cancer Center have developed a ...

An Institute for Value-Based Medicine regional event in Houston, Texas, covered inconsistencies with the integration of precision medicine in oncology practices, the evolution of treatment for ...

Discover the groundbreaking Cancer AI Alliance led by Fred Hutchinson and three other top cancer centers, utilizing patient data to revolutionize cancer care ...

Developed by the NanoBRIGHT project consortium, the new platform employs vibrational fiber photometry as a method to "image the cytoarchitecture of the mouse brain, monitor molecular alterations ...

An innovative technique, termed the 'molecular lantern', enables non-invasive monitoring of molecular changes in the brain, ...

Researchers want trustworthy, human-relevant models. Integrating automation and AI into organoid development workflows—or ...

Individuals with advanced breast cancer at diagnosis are more likely to have prevalent cardiovascular disease (CVD), ac ...

Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian ...

Farber, Memorial Sloan Kettering, The Sidney Kimmel Comprehensive Cancer Center and the Whiting School of Engineering at ...

Cancer immunotherapy drugs called immune checkpoint inhibitors take the brakes off the body’s immune system, allowing it to ...