Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
Visual inspection of histopathology slides is one of the main methods used by pathologists
to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and …
to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and …
Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks
Objective Non-small cell lung cancer is a leading cause of cancer death worldwide, and
histopathological evaluation plays the primary role in its diagnosis. However, the …
histopathological evaluation plays the primary role in its diagnosis. However, the …
Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study
H Yang, L Chen, Z Cheng, M Yang, J Wang, C Lin… - BMC medicine, 2021 - Springer
Background Targeted therapy and immunotherapy put forward higher demands for accurate
lung cancer classification, as well as benign versus malignant disease discrimination. Digital …
lung cancer classification, as well as benign versus malignant disease discrimination. Digital …
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
Classification of histologic patterns in lung adenocarcinoma is critical for determining tumor
grade and treatment for patients. However, this task is often challenging due to the …
grade and treatment for patients. However, this task is often challenging due to the …
A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images
F Kanavati, G Toyokawa, S Momosaki, H Takeoka… - Scientific reports, 2021 - nature.com
The differentiation between major histological types of lung cancer, such as
adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small-cell lung cancer …
adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small-cell lung cancer …
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
Lung cancer is the most prevalent cancer worldwide, and histopathological assessment is
indispensable for its diagnosis. However, human evaluation of pathology slides cannot …
indispensable for its diagnosis. However, human evaluation of pathology slides cannot …
DeepLRHE: a deep convolutional neural network framework to evaluate the risk of lung cancer recurrence and metastasis from histopathology images
Z Wu, L Wang, C Li, Y Cai, Y Liang, X Mo, Q Lu… - Frontiers in …, 2020 - frontiersin.org
It is critical for patients who cannot undergo eradicable surgery to predict the risk of lung
cancer recurrence and metastasis; therefore, the physicians can design the appropriate …
cancer recurrence and metastasis; therefore, the physicians can design the appropriate …
Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images
Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers
in lung cancer, with implications for patient prognosis and treatment decisions. Typically …
in lung cancer, with implications for patient prognosis and treatment decisions. Typically …
Deep learning for lung cancer detection: tackling the kaggle data science bowl 2017 challenge
We present a deep learning framework for computer-aided lung cancer diagnosis. Our multi-
stage framework detects nodules in 3D lung CAT scans, determines if each nodule is …
stage framework detects nodules in 3D lung CAT scans, determines if each nodule is …
A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets
P Mukherjee, M Zhou, E Lee, A Schicht… - Nature machine …, 2020 - nature.com
Lung cancer is the most common fatal malignancy in adults worldwide, and non-small-cell
lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography is …
lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography is …
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