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) ...

The study demonstrates that machine learning can achieve high performance on a challenging image classification task and has the potential to greatly assist pathologists in lung cancer classification.

Machine learning (ML) has the potential to transform oncology and, more broadly, medicine. 1 The introduction of ML in health care has been enabled by the digitization of patient data, including the ...

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.

Researchers review the application of machine learning in improving cancer diagnosis, treatment, and prognosis.

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

We illustrate the possible value of the mechanistic approach by performing predictive simulations of the entire cancer history of real patients, calibrated from data available at diagnosis only.

Machine learning algorithms can help predict positive resection margin and lymph node metastases among patients with pancreatic ductal adenocarcinoma, according to study results.The approach ...