AIMC Topic: Lung Neoplasms

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Development of a machine learning-based risk model for postoperative complications of lung cancer surgery.

Surgery today Jun 19, 2024
PURPOSE: To develop a comorbidity risk score specifically for lung resection surgeries.
Lung Neoplasms Pneumonectomy Risk Postoperative Complications Comorbidity ROC Curve Machine Learning Male Female Middle Aged Risk Factors Risk Assessment Aged Humans
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Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy.

Computer methods and programs in biomedicine Jun 19, 2024
BACKGROUND AND OBJECTIVE: To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve radiother...
Female Humans Aged Lung Neoplasms Tomography, X-Ray Computed Radiotherapy Dosage Male Middle Aged Multiomics Radiotherapy, Intensity-Modulated Deep Learning Radiation Pneumonitis
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A Multiscale Connected UNet for the Segmentation of Lung Cancer Cells in Pathology Sections Stained Using Rapid On-Site Cytopathological Evaluation.

The American journal of pathology Jun 17, 2024
Lung cancer is an increasingly serious health problem worldwide, and early detection and diagnosis are crucial for successful treatment. With the development of artificial intelligence and the growth of data volume, machine learning techniques can pl...
Humans Algorithms Deep Learning Lung Neoplasms Endoscopic Ultrasound-Guided Fine Needle Aspiration
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Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

Nature medicine Jun 14, 2024
In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (T...
Colorectal Neoplasms Biomarkers, Tumor Humans Machine Learning Circulating Tumor DNA DNA Copy Number Variations Tumor Burden Neoplasms Whole Genome Sequencing Neoplasm, Residual Lung Neoplasms Polymorphism, Single Nucleotide
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Decoding temporal heterogeneity in NSCLC through machine learning and prognostic model construction.

World journal of surgical oncology Jun 13, 2024
BACKGROUND: Non-small cell lung cancer (NSCLC) is a prevalent and heterogeneous disease with significant genomic variations between the early and advanced stages. The identification of key genes and pathways driving NSCLC tumor progression is critica...
Carcinoma, Non-Small-Cell Lung Single-Cell Analysis Lung Neoplasms Humans Gene Expression Regulation, Neoplastic Machine Learning Biomarkers, Tumor Disease Progression Prognosis Male Gene Expression Profiling Female Transcriptome
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The efficacy of machine learning models in lung cancer risk prediction with explainability.

PloS one Jun 13, 2024
Among many types of cancers, to date, lung cancer remains one of the deadliest cancers around the world. Many researchers, scientists, doctors, and people from other fields continuously contribute to this subject regarding early prediction and diagno...
Humans Lung Neoplasms Machine Learning Risk Assessment
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Histological Subtype Classification of Non-Small Cell Lung Cancer with Radiomics and 3D Convolutional Neural Networks.

Journal of imaging informatics in medicine Jun 11, 2024
Non-small cell lung carcinoma (NSCLC) is the most common type of pulmonary cancer, one of the deadliest malignant tumors worldwide. Given the increased emphasis on the precise management of lung cancer, identifying various subtypes of NSCLC has becom...
Imaging, Three-Dimensional Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Neural Networks, Computer Radiomics Tomography, X-Ray Computed Deep Learning
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Res-TransNet: A Hybrid deep Learning Network for Predicting Pathological Subtypes of lung Adenocarcinoma in CT Images.

Journal of imaging informatics in medicine Jun 11, 2024
This study aims to develop a CT-based hybrid deep learning network to predict pathological subtypes of early-stage lung adenocarcinoma by integrating residual network (ResNet) with Vision Transformer (ViT). A total of 1411 pathologically confirmed gr...
Humans Computer Simulation Retrospective Studies Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Adenocarcinoma of Lung Female Male Middle Aged
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Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.

Laboratory investigation; a journal of technical methods and pathology Jun 11, 2024
Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critical for the treatment of non-small cell lung cancer patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In ...
ErbB Receptors Eosine Yellowish-(YS) Hematoxylin Lung Neoplasms Carcinoma, Non-Small-Cell Lung Mutation Humans Female Middle Aged Deep Learning Aged Male
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Artificial intelligence-driven computer aided diagnosis system provides similar diagnosis value compared with doctors' evaluation in lung cancer screening.

BMC medical imaging Jun 11, 2024
OBJECTIVE: To evaluate the consistency between doctors and artificial intelligence (AI) software in analysing and diagnosing pulmonary nodules, and assess whether the characteristics of pulmonary nodules derived from the two methods are consistent fo...
Humans Retrospective Studies Tomography, X-Ray Computed Female Aged Neural Networks, Computer Artificial Intelligence Software Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted ROC Curve Lung Neoplasms Adult Male Middle Aged
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