AIMC Topic: Lung Neoplasms

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Potential of artificial intelligence based on chest computed tomography to predict the nature of part-solid nodules.

The clinical respiratory journal Feb 5, 2023
BACKGROUND: The potential of artificial intelligence (AI) to predict the nature of part-solid nodules based on chest computed tomography (CT) is still under exploration.
Artificial Intelligence Retrospective Studies Humans Lung Neoplasms Tomography, X-Ray Computed ROC Curve
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The Intersection of Lung Cancer Screening, Radiomics, and Artificial Intelligence: Can One Scan Really Predict the Future Development of Lung Cancer?

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Feb 3, 2023
Lung Neoplasms Early Detection of Cancer Humans Artificial Intelligence Machine Learning Forecasting
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Integration of artificial intelligence in lung cancer: Rise of the machine.

Cell reports. Medicine Feb 3, 2023
The goal of oncology is to provide the longest possible survival outcomes with the therapeutics that are currently available without sacrificing patients' quality of life. In lung cancer, several data points over a patient's diagnostic and treatment ...
Humans Quality of Life Lung Neoplasms Artificial Intelligence Precision Medicine
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Beyond the : Should Imaging-Based Risk Assessment Tools Be Used in Lung Cancer Screening?

AJR. American journal of roentgenology Feb 1, 2023
Humans Tomography, X-Ray Computed Lung Neoplasms Early Detection of Cancer Risk Assessment Deep Learning
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[Robot-assisted Lung Surgery: Techniques, Evidence and Data on Anatomical Resections].

Zentralblatt fur Chirurgie Jan 30, 2023
Thanks to improved visualisation and instruments with an endowrist function, robot-assisted thoracic surgery has led to technical progress in thoracic surgery. This makes it easier to carry out complex thoracic surgical interventions, e.g. with an in...
Humans Robotic Surgical Procedures Lung Neoplasms Thoracic Surgical Procedures Lung Robotics
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Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules.

Computational intelligence and neuroscience Jan 30, 2023
Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred to as metastasis. This work uses image processing, deep learning,...
Lung Humans Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Lung Neoplasms Tomography, X-Ray Computed
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Survival prediction for stage I-IIIA non-small cell lung cancer using deep learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 20, 2023
BACKGROUND AND PURPOSE: The aim of this study was to develop and evaluate a prediction model for 2-year overall survival (OS) in stage I-IIIA non-small cell lung cancer (NSCLC) patients who received definitive radiotherapy by considering clinical var...
Humans Retrospective Studies Tomography, X-Ray Computed Deep Learning Lung Neoplasms Neoplasm Staging Carcinoma, Non-Small-Cell Lung
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Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective.

Seminars in cancer biology Jan 20, 2023
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the world. The overall five-year survival rate of lung cancer is relatively lower than many leading cancers. Early diagnosis and prognosis of lung cancer are essen...
Artificial Intelligence Machine Learning Humans Lung Neoplasms
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A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society Jan 20, 2023
BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a first-line therapy for non-small cell lung cancer (NSCLC) with EGFR mutations. Approximately half of the patients with EGFR-mutated NSCLC are treated with...
Tyrosine Kinase Inhibitors Progression-Free Survival Disease-Free Survival ErbB Receptors Protein Kinase Inhibitors Carcinoma, Non-Small-Cell Lung Mutation Deep Learning Lung Neoplasms Humans
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Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer.

Clinical radiology Jan 14, 2023
AIM: To develop and validate a nomogram model that combines computed tomography (CT)-based radiological factors extracted from deep-learning and clinical factors for the early predictions of immune checkpoint inhibitor-related pneumonitis (ICI-P).
Risk Factors Pneumonia Humans Immune Checkpoint Inhibitors Deep Learning Lung Neoplasms Retrospective Studies
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