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 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.” ...

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 ...

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 ...

Using machine learning algorithms and human gut bacteria, scientists have developed a new low-cost screening method for detecting colorectal cancer.

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 ...

“Machine-Learning-Based Detection of an Ovarian Cancer Disease Fingerprint from Serum via Quantum Defect-Modified Carbon Nanotube Arrays.” Nature Biomedical Engineering (2022). Z Yaari, Y Yang, E ...