The artificial intelligence and machine learning in lung cancer immunotherapy
Q Gao, L Yang, M Lu, R **, H Ye, T Ma - Journal of Hematology & …, 2023 - Springer
Since the past decades, more lung cancer patients have been experiencing lasting benefits
from immunotherapy. It is imperative to accurately and intelligently select appropriate …
from immunotherapy. It is imperative to accurately and intelligently select appropriate …
Deep learning for lung cancer diagnosis, prognosis and prediction using histological and cytological images: a systematic review
Simple Summary Lung cancer is one of the most common and deadly malignancies
worldwide. Microscopic examination of histological and cytological lung specimens can be a …
worldwide. Microscopic examination of histological and cytological lung specimens can be a …
AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer
Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour
aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of …
aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of …
Histopathology images-based deep learning prediction of prognosis and therapeutic response in small cell lung cancer
Y Zhang, Z Yang, R Chen, Y Zhu, L Liu, J Dong… - NPJ digital …, 2024 - nature.com
Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer characterized
by rapid tumor growth and early metastasis. Accurate prediction of prognosis and …
by rapid tumor growth and early metastasis. Accurate prediction of prognosis and …
[HTML][HTML] Application of digital pathology and machine learning in the liver, kidney and lung diseases
B Wu, G Moeckel - Journal of Pathology Informatics, 2023 - Elsevier
The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for
the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the …
the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the …
Novel tools for early diagnosis and precision treatment based on artificial intelligence
J Shao, J Feng, J Li, S Liang, W Li… - Chinese Medical Journal …, 2023 - mednexus.org
Lung cancer has the highest mortality rate among all cancers in the world. Hence, early
diagnosis and personalized treatment plans are crucial to improving its 5-year survival rate …
diagnosis and personalized treatment plans are crucial to improving its 5-year survival rate …
[HTML][HTML] Next-generation lung cancer pathology: Development and validation of diagnostic and prognostic algorithms
Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors. In this
study, we develop a clinically useful computational pathology platform for NSCLC that can …
study, we develop a clinically useful computational pathology platform for NSCLC that can …
[HTML][HTML] Outcome-Supervised Deep Learning on Pathologic Whole Slide Images for Survival Prediction of Immunotherapy in Patients with Non–Small Cell Lung …
B Li, L Yang, H Zhang, H Li, C Jiang, Y Yao, S Cheng… - Modern Pathology, 2023 - Elsevier
Abstract Although programmed death-(ligand) 1 (PD-(L) 1) inhibitors are marked by durable
efficacy in patients with non–small cell lung cancer (NSCLC), approximately 60% of the …
efficacy in patients with non–small cell lung cancer (NSCLC), approximately 60% of the …
Whole slide image based deep learning refines prognosis and therapeutic response evaluation in lung adenocarcinoma
Existing prognostic models are useful for estimating the prognosis of lung adenocarcinoma
patients, but there remains room for improvement. In the current study, we developed a deep …
patients, but there remains room for improvement. In the current study, we developed a deep …
Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology
A deep learning model using attention-based multiple instance learning (aMIL) and self-
supervised learning (SSL) was developed to perform pathologic classification of …
supervised learning (SSL) was developed to perform pathologic classification of …