A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

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.

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 ...

The procedure is based around dynamic optical contrast microscopy (DOCI), a technique in development at UCLA since 2016. It ...

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 ...

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 ...

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 ...