Lung Adenocarcinoma

Lung adenocarcinoma, the most common type of lung cancer, is a heterogeneous disease with diverse growth patterns and molecular subtypes impacting prognosis and treatment response. Current research focuses on developing computational models, employing convolutional neural networks, transformer architectures, and other machine learning techniques, to analyze histopathology images (H&E and whole slide images) and CT scans for improved subtype classification, prediction of biomarkers like MET overexpression and EGFR mutation status, and ultimately, personalized treatment selection. These advancements aim to improve diagnostic accuracy, facilitate earlier and more precise interventions, and ultimately enhance patient outcomes by optimizing treatment strategies.