AIMC Topic: Carcinoma, Non-Small-Cell Lung

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[Experience of Thoracotomy and Robot-assisted Bronchial Sleeve Resection 
after Neoadjuvant Chemoimmunotherapy for Local Advanced Central Lung Cancer].

Zhongguo fei ai za zhi = Chinese journal of lung cancer Feb 20, 2022
BACKGROUND: Immunoneoadjuvant therapy opens a new prospect for local advanced lung cancer. The aim of our study was to explore the safety and feasibility of robotic-assisted bronchial sleeve resection in patients with locally advanced non-small cell ...
Neoadjuvant Therapy Carcinoma, Non-Small-Cell Lung Robotics Pneumonectomy Thoracotomy Humans Retrospective Studies Lung Neoplasms Treatment Outcome
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Efficacy and safety of carboplatin with nab-paclitaxel versus docetaxel in older patients with squamous non-small-cell lung cancer (CAPITAL): a randomised, multicentre, open-label, phase 3 trial.

The lancet. Healthy longevity Dec 1, 2021
BACKGROUND: In Japan, docetaxel, a cytotoxic monotherapy, is the standard drug administered to older patients with advanced non-small-cell lung cancer (NSCLC). Carboplatin plus nab-paclitaxel has shown a high objective response rate in patients with ...
Carboplatin Lung Neoplasms Humans Docetaxel Carcinoma, Squamous Cell Antineoplastic Combined Chemotherapy Protocols Aged Carcinoma, Non-Small-Cell Lung Leukopenia Aged, 80 and over Albumins Paclitaxel
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End-to-End Non-Small-Cell Lung Cancer Prognostication Using Deep Learning Applied to Pretreatment Computed Tomography.

JCO clinical cancer informatics Oct 1, 2021
PURPOSE: Clinical TNM staging is a key prognostic factor for patients with lung cancer and is used to inform treatment and monitoring. Computed tomography (CT) plays a central role in defining the stage of disease. Deep learning applied to pretreatme...
Tomography, X-Ray Computed Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Retrospective Studies
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Comparison between robot-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery for mediastinal and hilar lymph node dissection in lung cancer surgery.

Interactive cardiovascular and thoracic surgery Aug 18, 2021
OBJECTIVES: Lymph node dissection (LND) with robot-assisted thoracoscopic surgery (RATS) in lung cancer surgery has not been fully evaluated. The aim of this study was to compare LND surgical results between video-assisted thoracoscopic surgery (VATS...
Humans Lymph Node Excision Robotics Pneumonectomy Neoplasm Recurrence, Local Retrospective Studies Lung Neoplasms Lymph Nodes Carcinoma, Non-Small-Cell Lung Thoracic Surgery, Video-Assisted Mediastinum
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Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

American journal of respiratory and critical care medicine Aug 15, 2021
Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basi...
Odds Ratio Clinical Decision Rules Sensitivity and Specificity Male Middle Aged Case-Control Studies Retrospective Studies Humans ROC Curve Female Machine Learning Lung Neoplasms Aged Carcinoma, Non-Small-Cell Lung Aged, 80 and over Early Detection of Cancer
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Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Technology in cancer research & treatment Jan 1, 2021
Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinical behaviors of the two tumor types. We propose the use of a deep learning and transfer learning appr...
Diagnosis, Differential Image Interpretation, Computer-Assisted Small Cell Lung Carcinoma Lung Neoplasms Carcinoma, Non-Small-Cell Lung Follow-Up Studies Magnetic Resonance Imaging Machine Learning Prognosis Retrospective Studies Female Brain Neoplasms Male Middle Aged ROC Curve Humans
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Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Medicine Aug 21, 2020
Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Automatic segmentation of OARs based on convolutional neural network (CNN) has been established for lung cancer patients at our institution. The aim of th...
Humans Neural Networks, Computer Retrospective Studies Reproducibility of Results Lung Liver Radiotherapy Planning, Computer-Assisted Time Factors Esophagus Lung Neoplasms Spinal Cord Heart Carcinoma, Non-Small-Cell Lung Organs at Risk
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Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

Molecular imaging and biology Aug 1, 2020
PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung cancer (NSCLC) patients based on mutation status in the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene (KRAS). At the...
Algorithms Multivariate Analysis Area Under Curve ErbB Receptors Female Aged Mutation Proto-Oncogene Proteins p21(ras) Male Humans Positron-Emission Tomography Lung Neoplasms Machine Learning High-Throughput Nucleotide Sequencing Genomics Carcinoma, Non-Small-Cell Lung Multimodal Imaging
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Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks.

Journal of the American Medical Informatics Association : JAMIA May 1, 2020
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 morphological patterns associated with the molecular subtypes have not been sys...
Adenocarcinoma of Lung Humans Transcriptome Neural Networks, Computer ROC Curve Machine Learning Lung Neoplasms Carcinoma, Squamous Cell Carcinoma, Non-Small-Cell Lung
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The Relative Importance of Clinical and Socio-demographic Variables in Prognostic Prediction in Non-Small Cell Lung Cancer: A Variable Importance Approach.

Medical care May 1, 2020
BACKGROUND: Prognostic modeling in health care has been predominantly statistical, despite a rapid growth of literature on machine-learning approaches in biological data analysis. We aim to assess the relative importance of variables in predicting ov...
Humans Machine Learning Prognosis Radiopharmaceuticals Tumor Burden Male Carcinoma, Non-Small-Cell Lung Random Allocation Middle Aged Retrospective Studies Models, Statistical Whole Body Imaging Comorbidity Female Positron Emission Tomography Computed Tomography Lung Neoplasms Aged Neoplasm Staging Adult
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