EurekAlert!

A machine learning model that uses DNA methylation patterns may help identify the origin of cancers of unknown primary

A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types in patients with cancers of unknown primary (CUP), according to research ...

AACR: New platform uses machine learning to predict responses in patients with lung cancer

An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center ...

A deep learning pathomics platform may help predict response to immunotherapy in lung cancer patients

A biology-guided artificial intelligence model applied to routine pathology slides accurately predicted outcomes and response ...
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Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...
ascopubs.org

Machine Learning Model Integrating Computed Tomography Image–Derived Radiomics and Circulating miRNAs to Predict Residual Teratoma in Metastatic Nonseminoma Testicular Cancer

This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...
EurekAlert!

AI cancer tools risk “shortcut learning” rather than detecting true biology

New research warns that popular deep learning systems trained for cancer pathology may be relying on hidden shortcuts rather than genuine biological signals. Artificial intelligence tools are ...