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 classification ...

The review demonstrated a rise in publications related to AI/machine learning cancer pain research, with 1 article published between 2006 and 2009 and 26 published between 2020 and 2023. Artificial ...

Thyroid cancer is the most common endocrine cancer, affecting more people each year as detection rates continue to rise.

Noetik CEO and co-founder Ron Alfa, M.D., Ph.D., said the licensing of human foundation models is “a new paradigm in biotech.” With the GSK deal validating the paradigm, in Alfa’s view, Noetik ...

With the help of machine learning, scientists have identified a plethora of previously-unidentified drug targets for breast cancer, cervical cancer, glioblastoma and more. In a study published Jan. 11 ...

Pancreatic cancer (PaC) is often diagnosed at advanced stages, resulting in one of the lowest survival rates among patients with cancer. The purpose of this study was to investigate whether machine ...

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 ...

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) ...

Automated Classification of Breast Cancer Across the Spectrum of ERBB2 Expression Focusing on Heterogeneous Tumors With Low Human Epidermal Growth Factor Receptor 2 Expression We included patients age ...

Using machine learning and a large volume of data on genes and existing drugs, researchers at Lund University in Sweden have ...