AIMC Topic: Adenocarcinoma of Lung

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Identification of transcription factors that may reprogram lung adenocarcinoma.

Artificial intelligence in medicine
BACKGROUND: Lung adenocarcinoma is one of most threatening disease to human health. Although many efforts have been devoted to its genetic study, few researches have been focused on the transcription factors which regulate tumor initiation and progre...

Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: The aim of this study is to develop a deep learning-based multimodal feature interaction-guided fusion (DL-MFIF) framework that integrates macroscopic information from computed tomography (CT) images with microscopic informa...

The Critical Role of APOE+ Macrophages in the Immune Microenvironment and Prognosis of Lung Adenocarcinoma.

Journal of cellular and molecular medicine
The immunoregulatory functions and clinical implications of APOE+ macrophages within the tumour microenvironment of lung adenocarcinoma remain incompletely defined. In this study, single-cell transcriptome analysis revealed distinct subsets of APOE+ ...

Comprehensive Characterization of Somatic Mutation Timing Reveals the Evolutionary Trajectory of Lung Adenocarcinoma in Chinese Patients.

Cancer research
UNLABELLED: Lung adenocarcinoma (LUAD) is a heterogeneous disease with substantial genomic differences between individuals of Chinese and European ancestries. Deciphering the timing of driver mutations may lead to insights into tumor evolution that c...

Characterization of m6A-Related Genes in Tumor-Associated Macrophages for Prognosis, Immunotherapy, and Drug Prediction in Lung Adenocarcinomas Based on Machine Learning Algorithms.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Tumor-associated macrophages (TAMs) are a vital immune component within the tumor microenvironment (TME) of lung adenocarcinoma (LUAD), exerting significant influence on tumor growth, metastasis, and drug resistance. N6-methyladenosine (m6A) modifica...

CellOMaps: A compact representation for robust classification of lung adenocarcinoma growth patterns.

Computers in biology and medicine
Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease, characterized by five primary histological growth patterns. The classification of such patterns is crucial due to their direct relation to prognosis but the high subjectivity and ...

Deep learning radiomics fusion model to predict visceral pleural invasion of clinical stage IA lung adenocarcinoma: a multicenter study.

Journal of cardiothoracic surgery
AIM: To assess the predictive performance, risk stratification capabilities, and auxiliary diagnostic utility of radiomics, deep learning, and fusion models in identifying visceral pleural invasion (VPI) in lung adenocarcinoma.

Combining graph neural network and Mamba to capture local and global tissue spatial relationships in whole slide images.

Scientific reports
In computational pathology, extracting and representing spatial features from gigapixel whole slide images (WSIs) are fundamental tasks, but due to their large size, WSIs are typically segmented into smaller tiles. A critical aspect of analyzing WSIs...