AIMC Topic: Lung Neoplasms

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Recurrence patterns and prediction of survival after recurrence for gallbladder cancer.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract Feb 17, 2025
BACKGROUND: Gallbladder cancer (GBC) is associated with a poor prognosis. Recurrence patterns and their effect on survival remain ill-defined. This study aimed to analyze recurrence patterns and develop a machine learning (ML) model to predict surviv...
Gallbladder Neoplasms Cholecystectomy Male Retrospective Studies Lung Neoplasms Middle Aged Female Neoplasm Recurrence, Local Liver Neoplasms Aged Peritoneal Neoplasms Humans Machine Learning Prognosis
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A series of natural language processing for predicting tumor response evaluation and survival curve from electronic health records.

BMC medical informatics and decision making Feb 17, 2025
BACKGROUND: The clinical information housed within unstructured electronic health records (EHRs) has the potential to promote cancer research. The National Cancer Center Hospital (NCCH) is widely recognized as a leading institution for the treatment ...
Humans Natural Language Processing Electronic Health Records Japan Antineoplastic Agents Survival Analysis Lung Neoplasms
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Prior knowledge-based multi-task learning network for pulmonary nodule classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 16, 2025
The morphological characteristics of pulmonary nodule, also known as the attributes, are crucial for classification of benign and malignant nodules. In clinical, radiologists usually conduct a comprehensive analysis of correlations between different ...
Neural Networks, Computer Machine Learning Tomography, X-Ray Computed Humans Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted
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Unveiling the crucial role of glycosylation modification in lung adenocarcinoma metastasis through artificial neural network-based spatial multi-omics single-cell analysis and Mendelian randomization.

BMC cancer Feb 13, 2025
BACKGROUND: Investigations into the intricacies of glycosylation modifications, a prevalent post-translational alteration observed in neoplasms, especially remain elusive in the context of lung adenocarcinoma. Through the integration of multiple omic...
Transcriptome Single-Cell Analysis Lung Neoplasms Humans Multiomics Protein Processing, Post-Translational Neural Networks, Computer Gene Expression Regulation, Neoplastic Mendelian Randomization Analysis Gene Expression Profiling Adenocarcinoma of Lung Glycosylation
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Artificial intelligence-assisted point-of-care devices for lung cancer.

Clinica chimica acta; international journal of clinical chemistry Feb 11, 2025
Lung cancer is the leading cause of cancer-related deaths worldwide, primarily due to late-stage detection, which limits treatment options. Early detection and screening can increase survival rates, but traditional medical imaging methods are costly ...
Point-of-Care Systems Lung Neoplasms Biosensing Techniques Early Detection of Cancer Humans Artificial Intelligence Biomarkers, Tumor
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Deep learning paradigms in lung cancer diagnosis: A methodological review, open challenges, and future directions.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 11, 2025
Lung cancer is the leading cause of global cancer-related deaths, which emphasizes the critical importance of early diagnosis in enhancing patient outcomes. Deep learning has demonstrated significant promise in lung cancer diagnosis, excelling in nod...
Deep Learning Lung Neoplasms Neural Networks, Computer Diagnosis, Computer-Assisted Humans
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Multi-modality medical image classification with ResoMergeNet for cataract, lung cancer, and breast cancer diagnosis.

Computers in biology and medicine Feb 11, 2025
The variability in image modalities presents significant challenges in medical image classification, as traditional deep learning models often struggle to adapt to different image types, leading to suboptimal performance across diverse datasets. This...
Humans Female Multimodal Imaging Cataract Image Interpretation, Computer-Assisted Breast Neoplasms Deep Learning Lung Neoplasms
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Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study.

Journal of cardiothoracic surgery Feb 11, 2025
BACKGROUND: Radiomics has shown promise in the diagnosis and prognosis of lung cancer. Here, we investigated the performance of computed tomography-based radiomic features, extracted from gross tumor volume (GTV), peritumoral volume (PTV), and GTV + ...
Adenocarcinoma of Lung Middle Aged Lung Neoplasms Neoplasm Invasiveness Tomography, X-Ray Computed Female Aged Radiomics Cross-Sectional Studies Male Machine Learning Prognosis Retrospective Studies Humans
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Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.

Journal of medical systems Feb 11, 2025
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-small-cell lung cancer (NSCLC) using CT-based radiomics. We utilized two public data sets from the Cancer Imaging Archive (TCIA) ...
Humans Middle Aged Aged Deep Learning Radiomics Lung Neoplasms Carcinoma, Non-Small-Cell Lung Male Proportional Hazards Models Neural Networks, Computer Tomography, X-Ray Computed Female
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Differential gene expression analysis and machine learning identified structural, TFs, cytokine and glycoproteins, including SOX2, TOP2A, SPP1, COL1A1, and TIMP1 as potential drivers of lung cancer.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals Feb 10, 2025
BACKGROUND: Lung cancer is a primary global health concern, responsible for a considerable portion of cancer-related fatalities worldwide. Understanding its molecular complexities is crucial for identifying potential targets for treatment. The goal i...
Gene Regulatory Networks Lung Neoplasms Gene Expression Regulation, Neoplastic Biomarkers, Tumor Gene Expression Profiling Protein Interaction Maps SOXB1 Transcription Factors Poly-ADP-Ribose Binding Proteins Collagen Type I, alpha 1 Chain Humans DNA Topoisomerases, Type II Machine Learning Osteopontin Collagen Type I Tissue Inhibitor of Metalloproteinase-1
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