AIMC Topic: Lung Neoplasms

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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations.

Radiation oncology (London, England) Nov 25, 2024
BACKGROUND: Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKnife (CK) is essential for precise planning. We aim to employ deep learning to directly predict the 3D dose distribution calculated by the MC algorithm...
Lung Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiosurgery Monte Carlo Method Humans Algorithms Deep Learning
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CT ventilation images produced by a 3D neural network show improvement over the Jacobian and HU DIR-based methods to predict quantized lung function.

Medical physics Nov 23, 2024
BACKGROUND: Radiation-induced pneumonitis affects up to 33% of non-small cell lung cancer (NSCLC) patients, with fatal pneumonitis occurring in 2% of patients. Pneumonitis risk is related to the dose and volume of lung irradiated. Clinical radiothera...
Humans Imaging, Three-Dimensional Neural Networks, Computer Lung Neoplasms Tomography, X-Ray Computed Carcinoma, Non-Small-Cell Lung Lung Pulmonary Ventilation
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The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence.

Archivos de bronconeumologia Nov 22, 2024
In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and explore the contributions of artificial intelligence (AI), in overcoming them. We focus on evaluating th...
Deep Learning Lung Neoplasms Early Detection of Cancer Radiation Dosage Humans Artificial Intelligence Tomography, X-Ray Computed Pulmonary Disease, Chronic Obstructive
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Antigen-independent single-cell circulating tumor cell detection using deep-learning-assisted biolasers.

Biosensors & bioelectronics Nov 22, 2024
Circulating tumor cells (CTCs) in the bloodstream are important biomarkers for clinical prognosis of cancers. Current CTC identification methods are based on immuno-labeling, which depends on the differential expression of specific antigens between t...
Lasers Deep Learning Humans Biosensing Techniques Cell Line, Tumor Pancreatic Neoplasms Single-Cell Analysis Neoplastic Cells, Circulating Lung Neoplasms
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Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

Genes Nov 21, 2024
There exist significant challenges for lung adenocarcinoma (LUAD) due to its poor prognosis and limited treatment options, particularly in the advanced stages. It is crucial to identify genetic biomarkers for improving outcome predictions and guidin...
Male Protein Interaction Maps Humans Lung Neoplasms Computational Biology Machine Learning Gene Expression Regulation, Neoplastic Prognosis Kaplan-Meier Estimate Female Adenocarcinoma of Lung Biomarkers, Tumor
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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Scientific reports Nov 20, 2024
Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with poor survival rates and quality of life, making the timely identification of high-risk patients for BMs in ES-SCLC crucial. Patients diagnosed with E...
Small Cell Lung Carcinoma ROC Curve Lung Neoplasms Neoplasm Staging SEER Program Brain Neoplasms Male Middle Aged Humans Machine Learning Algorithms Prognosis Female Risk Factors Aged Adult
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

European radiology experimental Nov 20, 2024
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).
Middle Aged Deep Learning Lung Neoplasms Multiple Pulmonary Nodules Female Aged Male Solitary Pulmonary Nodule Emergency Service, Hospital Radiation Dosage Humans Artificial Intelligence Algorithms Prospective Studies Retrospective Studies Tomography, X-Ray Computed
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A systematic review on feature extraction methods and deep learning models for detection of cancerous lung nodules at an early stage -the recent trends and challenges.

Biomedical physics & engineering express Nov 20, 2024
Lung cancer is one of the most common life-threatening worldwide cancers affecting both the male and the female populations. The appearance of nodules in the scan image is an early indication of the development of cancer cells in the lung. The Low Do...
Image Processing, Computer-Assisted Lung Neoplasms Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Humans Lung Deep Learning Neural Networks, Computer Algorithms
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Prediction of benign and malignant pulmonary nodules using preoperative CT features: using PNI-GARS as a predictor.

Frontiers in immunology Nov 20, 2024
PURPOSE: The aim of this study was to develop and validate a prediction model for classification of pulmonary nodules based on preoperative CT imaging.
Tomography, X-Ray Computed Humans Female Machine Learning Aged Retrospective Studies Adult Multiple Pulmonary Nodules Solitary Pulmonary Nodule Male Middle Aged Lung Neoplasms
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A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.

Acta radiologica (Stockholm, Sweden : 1987) Nov 18, 2024
BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathological type of brain metastases (BMs).
Brain Retrospective Studies Female Aged Humans Magnetic Resonance Imaging Feasibility Studies Image Interpretation, Computer-Assisted Adenocarcinoma of Lung Multiparametric Magnetic Resonance Imaging Male Middle Aged Adult Deep Learning Radiomics Lung Neoplasms Brain Neoplasms
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