Researchers have developed a deep neural network to classify lung cancer subtypes on histopathology slides and found that it performed on par with three practicing pathologists. The study demonstrates ...

Machine learning (ML) models have been increasingly used in clinical oncology for cancer diagnosis, outcome predictions, and informing oncological therapy planning. The early identification and prompt ...

Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and Future Machine learning (ML) has the potential to transform oncology and, more broadly, ...

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) ...

In a recent study published in The Lancet Digital Health, researchers discuss the development and validation of a combined model comprising imaging, clinical, and cell-free deoxyribonucleic acid (DNA) ...

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

Clinical and pathological variables were collected in 431 patients, including tumor size, patient demographics, histological characteristics, molecular status, and staging information. A standard ...

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 has come of age in public health reporting. Researchers have found that existing algorithms and open source machine learning tools were as good as, or better than, human reviewers in ...