Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

Researchers explore DNA methylation patterns for early ovarian cancer detection, aiming to improve survival rates through ...

Researchers discuss the development and validation of a combined model for the early diagnosis of lung cancer.

On June 9, 2023, a new editorial paper was published in Oncoscience, entitled, “Transforming early cancer detection in primary care: harnessing the power of machine learning.” ...

The Science Translational Medicine study “Machine Learning to Detect the SINEs of Cancer” was supported by Burroughs Wellcome Career Award for Medical Scientists, National Institutes of Health ...

Aspyre Lung is a targeted biomarker panel of 114 genomic variants across 11 guideline-recommended genes with simultaneous DNA and RNA for non–small cell lung cancer (NSCLC). In this study, we ...

A straightforward blood test shows promise in accurately detecting ovarian cancer at its earliest stages, potentially ...

A predictive model utilizing serum metabolic profiles was able to distinguish ovarian cancer from control samples with 93% accuracy, according to a new study. Machine learning–based ...

POSTECH research team led by Professor Sanguk Kim proposes a machine learning (ML) model to accurately identify tissue-specific oncogenic driver mutations.

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. Breast ...