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 ...

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

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) ...

Computer scientists have secured funding to develop artificial intelligence that can automatically identify signs of early-stage oral cancer using an existing screening app.

Modeling frameworks exploit either canonical statistical approaches or artificial intelligence (AI) using machine learning (ML) classification algorithms. Prediction models have been explored using ...

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

They have found that existing algorithms and open source machine learning tools were as good as, or better than, human reviewers in detecting cancer cases using data from free-text pathology reports.