AIMC Topic: Lung Neoplasms

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Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.

JAMA network open Jul 1, 2021
IMPORTANCE: Electronic health records (EHRs) provide a low-cost means of accessing detailed longitudinal clinical data for large populations. A lung cancer cohort assembled from EHR data would be a powerful platform for clinical outcome studies.
Machine Learning Algorithms Prognosis Electronic Health Records Lung Neoplasms Humans Area Under Curve Survival Analysis Survivors Boston Female Male Cohort Studies ROC Curve
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Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

European journal of cancer (Oxford, England : 1990) Jun 26, 2021
OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients with non-small-cell lung cancer (NSCLC), but only some patients respond to the treatment. Various clinical characteristics, including the PD-ligand 1 (...
Aged Humans Middle Aged Aged, 80 and over Machine Learning Immune Checkpoint Inhibitors Adult Female Lung Neoplasms Male Carcinoma, Non-Small-Cell Lung
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Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers.

Computational and mathematical methods in medicine Jun 26, 2021
Lung cancer has a high mortality rate. Promoting early diagnosis and screening of lung cancer is the most effective way to enhance the survival rate of lung cancer patients. Through computer technology, a comprehensive evaluation of genetic testing r...
Middle Aged Early Detection of Cancer Case-Control Studies Lung Neoplasms Diagnosis, Computer-Assisted Aged, 80 and over Computational Biology ROC Curve Humans Adult Support Vector Machine Retrospective Studies Biomarkers, Tumor DNA Methylation Female Male Aged
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Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

Cancer imaging : the official publication of the International Cancer Imaging Society Jun 23, 2021
BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-trivial task requiring much expertise and time. A deep learning-based algorithm has the potential to assist with rapid and consistent lesion measurement...
Female Aged Male Deep Learning Lung Neoplasms Humans Retrospective Studies Tomography, X-Ray Computed
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Machine learning-based CT radiomics features for the prediction of pulmonary metastasis in osteosarcoma.

The British journal of radiology Jun 19, 2021
OBJECTIVE: This study aims to build machine learning-based CT radiomic features to predict patients developing metastasis after osteosarcoma diagnosis.
Osteosarcoma Bone Neoplasms Predictive Value of Tests Adolescent Child, Preschool Child Lung Neoplasms Young Adult Adult Male Middle Aged Machine Learning Humans Retrospective Studies Tomography, X-Ray Computed Female
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The predictive power of artificial intelligence on mediastinal lymphnode metastasis.

General thoracic and cardiovascular surgery Jun 16, 2021
OBJECTIVE: The aim of this study was to create the preoperative predictive model on mediastinal lymph-node metastasis based on artificial intelligence in surgically resected lung adenocarcinoma.
Humans Fluorodeoxyglucose F18 Artificial Intelligence Retrospective Studies Lung Neoplasms Lymph Nodes Lymphatic Metastasis Neoplasm Staging Positron-Emission Tomography
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Ultrasensitive detection of circulating tumour DNA via deep methylation sequencing aided by machine learning.

Nature biomedical engineering Jun 15, 2021
The low abundance of circulating tumour DNA (ctDNA) in plasma samples makes the analysis of ctDNA biomarkers for the detection or monitoring of early-stage cancers challenging. Here we show that deep methylation sequencing aided by a machine-learning...
Humans Early Detection of Cancer Machine Learning High-Throughput Nucleotide Sequencing Circulating Tumor DNA Case-Control Studies Lung Neoplasms Sequence Analysis, DNA DNA Methylation Adult Biomarkers, Tumor Male Middle Aged Female
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A comparison of the fusion model of deep learning neural networks with human observation for lung nodule detection and classification.

The British journal of radiology Jun 11, 2021
OBJECTIVES: To compare the diagnostic performance of a newly developed artificial intelligence (AI) algorithm derived from the fusion of convolution neural networks (CNN) versus human observers in the estimation of malignancy risk in pulmonary nodule...
Imaging, Three-Dimensional Lung Neoplasms Contrast Media Radiographic Image Interpretation, Computer-Assisted Adult Male Middle Aged Deep Learning Iohexol Observation Humans Tomography, X-Ray Computed Female Aged Aged, 80 and over
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AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.

European radiology Jun 4, 2021
OBJECTIVE: Assess if deep learning-based artificial intelligence (AI) algorithm improves reader performance for lung cancer detection on chest X-rays (CXRs).
Radiography Humans Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Radiography, Thoracic Algorithms Sensitivity and Specificity Lung Lung Neoplasms
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Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports.

Chest Jun 4, 2021
BACKGROUND: There is an urgent need for population-based studies on managing patients with pulmonary nodules.
Tomography, X-Ray Computed Sensitivity and Specificity Lung Lung Neoplasms Humans Algorithms Radiography, Thoracic Dimensional Measurement Accuracy Radiology Tumor Burden Quality Improvement Documentation Multiple Pulmonary Nodules Solitary Pulmonary Nodule Calcinosis Natural Language Processing
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