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Deep learning to estimate lung disease mortality from chest radiographs

Nature communications, 2023-05, Vol.14 (1), p.2797-10, Article 2797

2023

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Deep Learning to Estimate Biological Age From Chest Radiographs

JACC. Cardiovascular imaging, 2021-11, Vol.14 (11), p.2226-2236

2021

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Feasibility of lung cancer prediction from low-dose CT scan and smoking factors using causal models

Thorax, 2019-07, Vol.74 (7), p.643-649

2019

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Biomarker identification for statin sensitivity of cancer cell lines

Biochemical and biophysical research communications, 2018-01, Vol.495 (1), p.659-665

2018

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Pericardial disease in patients treated with immune checkpoint inhibitors

Journal for immunotherapy of cancer, 2021-06, Vol.9 (6), p.e002771

2021

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Can deep learning classify stroke subtypes from chest X-rays?

EBioMedicine, 2021-08, Vol.70, p.103517-103517, Article 103517

2021

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Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers

Communications medicine, 2024-03, Vol.4 (1), p.44-44, Article 44

2024

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Association Between Immune Checkpoint Inhibitors with Cardiovascular Events and Atherosclerotic Plaque

Circulation (New York, N.Y.), 2020-12, Vol.142 (24), p.2299-2311

2020

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Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model

Annals of internal medicine, 2020-11, Vol.173 (9), p.704-713

2020

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Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome

Radiology, 2023-02, Vol.306 (2), p.e221926-e221926

2023

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Microvascular Outcomes in Women With a History of Hypertension in Pregnancy

Circulation (New York, N.Y.), 2022-02, Vol.145 (7), p.552-554

2022

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Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations

Radiology, 2022-10, Vol.305 (1), p.212877-218

2022

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Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature

Circulation (New York, N.Y.), 2022-01, Vol.145 (2), p.134-150

2022

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Immune checkpoint inhibitors for cancer and venous thromboembolic events

European journal of cancer (1990), 2021-11, Vol.158, p.99-110

2021

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piMGM: incorporating multi-source priors in mixed graphical models for learning disease networks

Bioinformatics, 2018-09, Vol.34 (17), p.i848-i856

2018

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Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs: A Risk Prediction Study

Annals of internal medicine, 2024-04, Vol.177 (4), p.409-417

2024

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CausalMGM: an interactive web-based causal discovery tool

Nucleic acids research, 2020-07, Vol.48 (W1), p.W597-W602

2020

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Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis

Bioinformatics, 2019-04, Vol.35 (7), p.1204-1212

2019

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Deep Learning to Predict Mortality After Cardiothoracic Surgery Using Preoperative Chest Radiographs

The Annals of thoracic surgery, 2023-01, Vol.115 (1), p.257-264

2023

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Chest Radiographs: A New Form of Identification?

Radiology. Artificial intelligence, 2023-11, Vol.5 (6), p.e230397

2023

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Detection of high-frequency oscillations by hybrid depth electrodes in standard clinical intracranial EEG recordings

Frontiers in neurology, 2014-01, Vol.5, p.149-149

2014

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Integrated Theory-and Data-Driven Feature Selection in Gene Expression Data Analysis

2017 IEEE 33rd International Conference on Data Engineering (ICDE), 2017, p.1525-1532

2017

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External Testing of a Deep Learning Model to Estimate Biologic Age Using Chest Radiographs

Radiology. Artificial intelligence, 2024-09, Vol.6 (5), p.e230433

2024

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Neurological Complications Acquired During Pediatric Critical Illness: Exploratory “Mixed Graphical Modeling” Analysis Using Serum Biomarker Levels

Pediatric critical care medicine, 2021-10, Vol.22 (10), p.906-914

2021

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Deep learning to estimate lung disease mortality from chest radiographs

Deep Learning to Estimate Biological Age From Chest Radiographs

Feasibility of lung cancer prediction from low-dose CT scan and smoking factors using causal models

Biomarker identification for statin sensitivity of cancer cell lines

Pericardial disease in patients treated with immune checkpoint inhibitors

Can deep learning classify stroke subtypes from chest X-rays?

Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers

Association Between Immune Checkpoint Inhibitors with Cardiovascular Events and Atherosclerotic Plaque

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome

Microvascular Outcomes in Women With a History of Hypertension in Pregnancy

Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations

Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature

Immune checkpoint inhibitors for cancer and venous thromboembolic events

piMGM: incorporating multi-source priors in mixed graphical models for learning disease networks

Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs: A Risk Prediction Study

CausalMGM: an interactive web-based causal discovery tool

Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis

Deep Learning to Predict Mortality After Cardiothoracic Surgery Using Preoperative Chest Radiographs

Chest Radiographs: A New Form of Identification?

Detection of high-frequency oscillations by hybrid depth electrodes in standard clinical intracranial EEG recordings

Integrated Theory-and Data-Driven Feature Selection in Gene Expression Data Analysis

Enhancing Precision in Detecting Severe Immune-Related Adverse Events: Comparative Analysis of Large Language Models and International Classification of Disease Codes in Patient Records

External Testing of a Deep Learning Model to Estimate Biologic Age Using Chest Radiographs

Neurological Complications Acquired During Pediatric Critical Illness: Exploratory “Mixed Graphical Modeling” Analysis Using Serum Biomarker Levels

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