… Also, our results suggest that deep learning of histopathological imaging features can
predict the prognosis of lung cancer patients, thereby assisting health professionals to make …

… image tiles from the whole slide histopathology image of NSCLC to conduct the image …
classify each tile representation into either recurrence or non-recurrence. The authors first build a …

… Predicting tumor recurrence and survival for lung cancer patients is important in treatment …
complexity of lung cancer pathology images, predicting patient outcome from lung cancer WSI …

… b The percentage histogram showing the recurrence and non-recurrence proportion in low-,
… d The percentage histogram showing the recurrence and non-recurrence proportion in low-, …

… To study the prediction of gene mutations from histopathology images, we modified the
inception v3 to perform multitask classification rather than a single-task classification. Each …

… When cancer recurrence was suspected on chest CT images, … resonance imaging (MRI) and
other imaging techniques were … NSCLC, brain assessment with imaging at 6 and 12 months …

… network (CNN) using multi-scale pathology images to predict the prognosis of patients
with … no LUAD recurrence prediction studies have been published that incorporate image-based …

… pathology images to create a unified predictor of recurrence in early stage NSCLC. Additionally
we show in this work that the combination of radiomic and pathomic features allows for …

… metastasis and recurrence, has brought a significantly … stained pathological images of lung
cancer tissues, as well as to … 180 whole slice images (WSIs) of lung cancer downloaded from …

… lung cancer … cancer patients with H&E-stained histological images were downloaded from
the TCGA database. 26% of the patients were younger than 50 years old when breast cancer …