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 ...
Managed Healthcare Executive

CT feature combinations improve identification of interstitial lung disease patterns

Specific combinations of CT imaging features rather than individual findings alone may improve the accuracy of identifying ...
ascopubs.org

Machine learning model integrating CT radiomics and circulating microRNAs to predict residual disease histology in metastatic non-seminoma testicular cancer (mNSTC).

Circulating tumor DNA as a prognostic biomarker to predict retroperitoneal histology in patients undergoing retroperitoneal lymph node dissection. AUC values of different ML algorithms on training and ...
Yale Environment 360

Machine learning model predicts PTSD symptom severity over time

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...