Artificial intelligence (AI) can determine the course and severity of aggressive skin cancers, such as Merkel cell carcinoma (MCC), to enhance clinical decision making by generating personalized predictions of treatment specific outcomes for patients and their doctors, ScienceDaily reports.

An international team, led by researchers at Newcastle University, UK, combined machine learning with clinical expertise to develop a web-based system called "DeepMerkel" which offers the power to predict MCC treatment specific outcomes based on personal and tumor specific features.

They propose that this system could be applied to other aggressive skin cancers for precision prognostication, the enhancement of informed clinical decision making and improved patient choice.

In two complementary publications in Nature Digital Medicine and the Journal of the American Academy of Dermatology, the team describe how using advanced statistical and machine learning methods they developed the web-based prognostic tool for MCC.

In Nature Digital Medicine, the team describe how they employed explainability analysis and the data of to reveal new insights into mortality risk factors for the highly aggressive cancer, MCC. They then combined deep learning feature selection with a modified XGBoost framework, to develop a web-based prognostic tool for MCC which they termed DeepMerkel.

Analyzing the data from nearly 11,000 patients in two countries, the researchers describe in the Journal of the American Academy of Dermatology how DeepMerkel was able to accurately identify high-risk patients at an earlier stage of the cancer. This allows medics to make more informed decisions about when to use radical treatment options and intensive disease monitoring.