Laura Maguire

TL;DR: In this paper, the authors developed models to stratify patients by risk of severe outcomes during COVID-19 hospitalization using readily available information at hospital admission, including basic patient characteristics, vital signs at admission, and basic lab results collected at time of presentation.

TL;DR: In this article, the authors calculate and discuss the interpretation of exact Shapley values for a multivariate molecular diagnostic test in clinical use (the VeriStrat® test), and employ some standard approximation techniques for Shapley value computation (local interpretable model-agnostic explanation (LIME) and Shapley Additive Explanations (SHAP) based methods) and compare the results with exact ShapLEY values.

TL;DR: In this article, the authors developed models to stratify patients by risk of severe outcomes during COVID-19 hospitalization using readily available information at hospital admission, including basic patient characteristics, vital signs at admission, and basic lab results collected at time of presentation.

TL;DR: Kowanetz et al. as discussed by the authors applied the anti-PD-L1 Response Test (ART) to the larger OAK NSCLC Ph3 clinical study to investigate the interplay between tumor PDL1 expression and ART classifications in predicting outcomes and benefit from A therapy.

TL;DR: In this paper, a method for predicting whether an early stage (IA, IB) non-small-cell lung cancer (NSCLC) patient is at a high risk of recurrence of the cancer following surgery involves subjecting a blood-based sample from the patient (obtained prior to, at, or after the surgery) to mass spectrometry and classification with a computer implementing a classifier.