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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)
Heart, Lung, Blood and Sleep Disorders
Last data update: Apr 30, 2024
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Developing the Lung Graph-Based Machine Learning Model for Identification of Fibrotic Interstitial Lung Diseases.
Haishuang Sun et al. J Imaging Inform Med 2024
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Prevalence and clinical characteristics of patients with rheumatoid arthritis with interstitial lung disease using unstructured healthcare data and machine learning.
Jose A Román Ivorra et al. RMD Open 2024 10(1)
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Using random forest machine learning on data from a large, representative cohort of the general population improves clinical spirometry references.
Kris Kristensen et al. Clin Respir J 2023
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Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV decline: results from COPDGene and SPIROMICS.
Jennifer M Wang et al. Front Physiol 2023 141144192
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Development and validation of a respiratory-responsive vocal biomarker-based tool for generalizable detection of respiratory impairment: independent case-control studies in multiple respiratory conditions including asthma, chronic obstructive pulmonary disease, and COVID-19.
Savneet Kaur et al. Journal of medical Internet research 2023
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A transparent artificial intelligence framework to assess lung disease in pulmonary hypertension.
Michail Mamalakis et al. Scientific reports 2023 13(1) 3812
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Research Progress of Respiratory Disease and Idiopathic Pulmonary Fibrosis Based on Artificial Intelligence.
Gerui Zhang et al. Diagnostics (Basel, Switzerland) 2023 13(3)
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Use of big data on the social determinants of TB to find the "missing millions".
Biermann O et al. The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease 2022 26(12) 1194-1196
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Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population.
Liu Qing et al. BMC pulmonary medicine 2022 22(1) 327
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Use of illness severity scores to predict mortality in interstitial lung disease patients hospitalised with acute respiratory deterioration
RL WIlliams et al, MEDRXIV, July 12, 2022
Impact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease.
Röhrich Sebastian et al. European radiology 2022
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Exploring the most important factors related to self-perceived health among older men in Sweden: a cross-sectional study using machine learning.
Olsson Max et al. BMJ open 2022 12(6) e061242
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Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-resolution Computed Tomography.
Walsh Simon Lf et al. American journal of respiratory and critical care medicine 2022
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Predicting Usual Interstitial Pneumonia Histopathology from Chest CT with Deep Learning.
Bratt Alex et al. Chest 2022
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MIXTURE of human expertise and deep learning-developing an explainable model for predicting pathological diagnosis and survival in patients with interstitial lung disease.
Uegami Wataru et al. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc 2022
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Contemporary Clinical and Coronary Anatomic Risk Model for 30-Day Mortality After Percutaneous Coronary Intervention.
Doll Jacob A et al. Circulation. Cardiovascular interventions 2021 CIRCINTERVENTIONS121010863
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AI in predicting COPD in the Canadian population.
Zafari Hasan et al. Bio Systems 2021 104585
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Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.
Choe Jooae et al. Radiology 2021 204164
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Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach.
Spiegel Jerry M et al. Annals of global health 2021 87(1) 58
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Does machine learning have a role in the prediction of asthma in children?
Patel Dimpalben et al. Paediatric respiratory reviews 2021
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Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network.
Hasenstab Kyle A et al. Radiology. Cardiothoracic imaging 2021 3(2) e200477
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Application of logistic regression and convolutional neural network in prediction and diagnosis of high-risk populations of lung cancer.
Yuan Huijie et al. European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP) 2021
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Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example.
Angelini Elsa et al. Mycopathologia 2021
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Tuberculosis Diagnostics and Localization in Chest X-Rays via Deep Learning Models.
Guo Ruihua et al. Frontiers in artificial intelligence 2021 3583427
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Artificial intelligence/machine learning in respiratory medicine and potential role in asthma and COPD diagnosis.
Kaplan Alan et al. The journal of allergy and clinical immunology. In practice 2021
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The Emerging Role of Quantification of Imaging for Assessing the Severity and Disease Activity of Emphysema, Airway Disease, and Interstitial Lung Disease.
Goldin Jonathan Gerald et al. Respiration; international review of thoracic diseases 2021 1-14
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Neuromorphic on-chip recognition of saliva samples of COPD and healthy controls using memristive devices.
Zarrin Pouya Soltani et al. Scientific reports 2020 Nov 10(1) 19742
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Elastic Registration-driven Deep Learning for Longitudinal Assessment of Systemic Sclerosis Interstitial Lung Disease at CT.
Chassagnon Guillaume et al. Radiology 2020 Oct 200319
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Toward Early Severity Assessment of Obstructive Lung Disease Using Multi-Modal Wearable Sensor Data Fusion During Walking.
Rahman Md Juber et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2020 Jul 20205935-5938
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Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.
Harmon Stephanie A et al. Nature communications 2020 Aug 11(1) 4080
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 30, 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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