AIMC Topic: Lung Neoplasms

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Predicting Survival and Recurrence of Lung Ablation Patients Using Deep Learning-Based Automatic Segmentation and Radiomics Analysis.

Cardiovascular and interventional radiology Nov 27, 2024
PURPOSE: To predict survival and tumor recurrence following image-guided thermal ablation (IGTA) of lung tumors segmented using a deep learning approach.
Middle Aged Lung Deep Learning Lung Neoplasms Surgery, Computer-Assisted Neoplasm Recurrence, Local Ablation Techniques Female Aged Humans Radiomics Retrospective Studies Male Tomography, X-Ray Computed
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A Predictive Model Integrating AI Recognition Technology and Biomarkers for Lung Nodule Assessment.

The Thoracic and cardiovascular surgeon Nov 26, 2024
BACKGROUND:  Lung cancer is the most prevalent and lethal cancer globally, necessitating accurate differentiation between benign and malignant pulmonary nodules to guide treatment decisions. This study aims to develop a predictive model that integrat...
Solitary Pulmonary Nodule Neoplasm Invasiveness Predictive Value of Tests Risk Factors Aged Biomarkers, Tumor Male Middle Aged Retrospective Studies Lung Neoplasms Tomography, X-Ray Computed Multiple Pulmonary Nodules Female Humans Reproducibility of Results Artificial Intelligence Decision Support Techniques
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Application of NotebookLM, a large language model with retrieval-augmented generation, for lung cancer staging.

Japanese journal of radiology Nov 25, 2024
PURPOSE: In radiology, large language models (LLMs), including ChatGPT, have recently gained attention, and their utility is being rapidly evaluated. However, concerns have emerged regarding their reliability in clinical applications due to limitatio...
Large Language Models Lung Humans Lung Neoplasms Neoplasm Staging Tomography, X-Ray Computed Japan Reproducibility of Results
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Effect of Artificial Intelligence as a Second Reader on the Lung Nodule Detection and Localization Accuracy of Radiologists and Non-radiology Physicians in Chest Radiographs: A Multicenter Reader Study.

Academic radiology Nov 25, 2024
RATIONALE AND OBJECTIVES: Missed nodules in chest radiographs (CXRs) are common occurrences. We assessed the effect of artificial intelligence (AI) as a second reader on the accuracy of radiologists and non-radiology physicians in lung nodule detecti...
Humans Male Female Middle Aged Radiologists Lung Neoplasms Reproducibility of Results Artificial Intelligence Radiographic Image Interpretation, Computer-Assisted Aged Retrospective Studies Solitary Pulmonary Nodule Observer Variation Sensitivity and Specificity Tomography, X-Ray Computed Radiography, Thoracic
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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...
Humans Algorithms Deep Learning Lung Neoplasms Radiosurgery Monte Carlo Method Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated
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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 Neural Networks, Computer Lung Neoplasms Tomography, X-Ray Computed Carcinoma, Non-Small-Cell Lung Lung Pulmonary Ventilation Imaging, Three-Dimensional
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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 Humans Lung Neoplasms Artificial Intelligence Early Detection of Cancer Tomography, X-Ray Computed Radiation Dosage 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...
Humans Biosensing Techniques Pancreatic Neoplasms Neoplastic Cells, Circulating Lasers Deep Learning Cell Line, Tumor Single-Cell Analysis 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...
Gene Expression Regulation, Neoplastic Kaplan-Meier Estimate Adenocarcinoma of Lung Protein Interaction Maps Humans Lung Neoplasms Machine Learning Computational Biology Prognosis Female Biomarkers, Tumor Male
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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...
Machine Learning Lung Neoplasms Algorithms Neoplasm Staging Prognosis SEER Program Humans Female Small Cell Lung Carcinoma Male Risk Factors Middle Aged Aged ROC Curve Adult Brain Neoplasms
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