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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: Apr 19, 2024
. (Total: 63627 Documents since 2012)
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Construction of a predictive model for bone metastasis from first primary lung adenocarcinoma within 3 cm based on machine learning algorithm: a retrospective study.
Yu Zhang et al. PeerJ 2024 12e17098
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Telemedicine-Enhanced Lung Cancer Screening Using Mobile Computed Tomography Unit with Remote Artificial Intelligence Assistance in Underserved Communities: Initial Results of a Population Cohort Study in Western China.
Wenjuan Tao et al. Telemed J E Health 2024
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Potential of radiomics analysis and machine learning for predicting brain metastasis in newly diagnosed lung cancer patients.
S Yichu et al. Clin Radiol 2024
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Exploring pollutant joint effects in disease through interpretable machine learning.
Shuo Wang et al. J Hazard Mater 2024 467133707
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Real-World Effectiveness of Lung Cancer Screening Using Deep Learning-Based Counterfactual Prediction.
Zheng Feng et al. Stud Health Technol Inform 2024 310419-423
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Predicting Phase 1 Lymphoma Clinical Trial Durations Using Machine Learning: An In-Depth Analysis and Broad Application Insights.
Bowen Long et al. Clin Pract 2024 14(1) 69-88
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Editorial: World lung cancer awareness month 2022: artificial intelligence for clinical management of lung cancer.
Parul Agarwal et al. Front Oncol 2024 131351016
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Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.
Matthew T Warkentin et al. Thorax 2024
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Air quality and cancer risk in the All of Us Research Program.
Andrew Craver et al. Cancer Causes Control 2023
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Clinico-biological-radiomics (CBR) based machine learning for improving the diagnostic accuracy of FDG-PET false-positive lymph nodes in lung cancer.
Caiyue Ren et al. Eur J Med Res 2023 28(1) 554
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Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans.
Ward Hendrix et al. Commun Med (Lond) 2023 3(1) 156
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Machine Learning Techniques to Predict Timeliness of Care among Lung Cancer Patients.
Arul Earnest et al. Healthcare (Basel) 2023 11(20)
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A Machine Learning-Based Model to Predict In-Hospital Mortality of Lung Cancer Patients: A Population-Based Study of 523,959 Cases.
Que N N Tran et al. Adv Respir Med 2023 91(4) 310-323
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Predicting lung cancer survival based on clinical data using machine learning: A review.
Fatimah Abdulazim Altuhaifa et al. Comput Biol Med 2023 165107338
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Machine learning strengthened prediction of tracheal, bronchus, and lung cancer deaths due to air pollution.
Jagadish Kumar Mogaraju et al. Environ Sci Pollut Res Int 2023
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Explainable Artificial Intelligence to Identify Dosimetric Predictors of Toxicity in Patients with Locally Advanced Non-Small Cell Lung Cancer: A Secondary Analysis of RTOG 0617.
Colton Ladbury et al. Int J Radiat Oncol Biol Phys 2023
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PET Radiomics and Response to Immunotherapy in Lung Cancer: A Systematic Review of the Literature.
Laura Evangelista et al. Cancers (Basel) 2023 15(12)
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Deep-Learning Model of ResNet Combined with CBAM for Malignant-Benign Pulmonary Nodules Classification on Computed Tomography Images.
Yanfei Zhang et al. Medicina (Kaunas) 2023 59(6)
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Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study.
Andrea G Rockall et al. Invest Radiol 2023
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Construction of the XGBoost model for early lung cancer prediction based on metabolic indices.
Xiuliang Guan et al. BMC Med Inform Decis Mak 2023 23(1) 107
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Benchmarking machine learning approaches to predict radiation-induced toxicities in lung cancer patients.
Francisco J Núñez-Benjumea et al. Clin Transl Radiat Oncol 2023 41100640
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Integration of Radiomics and Tumor Biomarkers in Interpretable Machine Learning Models.
Lennart Brocki et al. Cancers (Basel) 2023 15(9)
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Bayesian network enables interpretable and state-of-the-art prediction of immunotherapy responses in cancer patients.
Hideki Hozumi et al. PNAS Nexus 2023 2(5) pgad133
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Predictive power of deep-learning segmentation based prognostication model in non-small cell lung cancer.
Jordan C Gainey et al. Front Oncol 13868471
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Development and validation of a deep transfer learning-based multivariable survival model to predict overall survival in lung cancer.
Feng Zhu et al. Transl Lung Cancer Res 2023 12(3) 471-482
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Longitudinal lung cancer prediction convolutional neural network model improves the classification of indeterminate pulmonary nodules.
Rafael Paez et al. Sci Rep 2023 13(1) 6157
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Prediction of Brain Metastases Development in Patients With Lung Cancer by Explainable Artificial Intelligence From Electronic Health Records.
Zhao Li et al. JCO clinical cancer informatics 2023 7e2200141
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An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial.
Huiwen Xu et al. JAMA network open 2023 6(3) e234198
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Recalibration of a Deep Learning Model for Low-Dose Computed Tomographic Images to Inform Lung Cancer Screening Intervals.
Rebecca Landy et al. JAMA network open 2023 6(3) e233273
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Using Recurrent Neural Networks to Extract High-Quality Information From Lung Cancer Screening Computerized Tomography Reports for Inter-Radiologist Audit and Feedback Quality Improvement.
Yucheng Zhang et al. JCO clinical cancer informatics 2023 7e2200153
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 19, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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