Co-Author
This page shows the publications co-authored by Michael Lu and Hugo Aerts.
Connection Strength
1.450
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Deep Learning to Estimate Biological Age From Chest Radiographs. JACC Cardiovasc Imaging. 2021 11; 14(11):2226-2236.
Score: 0.232
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Deep-learning system to improve the quality and efficiency of volumetric heart segmentation for breast cancer. NPJ Digit Med. 2021 Mar 05; 4(1):43.
Score: 0.231
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Deep convolutional neural networks to predict cardiovascular risk from computed tomography. Nat Commun. 2021 01 29; 12(1):715.
Score: 0.229
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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. Ann Intern Med. 2020 11 03; 173(9):704-713.
Score: 0.223
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Deep Learning to Assess Long-term Mortality From Chest Radiographs. JAMA Netw Open. 2019 07 03; 2(7):e197416.
Score: 0.206
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Radiologists can visually predict mortality risk based on the gestalt of chest radiographs comparable to a deep learning network. Sci Rep. 2021 10 01; 11(1):19586.
Score: 0.060
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Small whole heart volume predicts cardiovascular events in patients with stable chest pain: insights from the PROMISE trial. Eur Radiol. 2021 Aug; 31(8):6200-6210.
Score: 0.057
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Epicardial Adipose Tissue in Patients With Stable Chest Pain: Insights From the PROMISE Trial. JACC Cardiovasc Imaging. 2020 10; 13(10):2273-2275.
Score: 0.056
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Radiomics of Coronary Artery Calcium in the Framingham Heart Study. Radiol Cardiothorac Imaging. 2020 Feb 27; 2(1):e190119.
Score: 0.054
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Radiomics versus Visual and Histogram-based Assessment to Identify Atheromatous Lesions at Coronary CT Angiography: An ex Vivo Study. Radiology. 2019 10; 293(1):89-96.
Score: 0.052
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Density and morphology of coronary artery calcium for the prediction of cardiovascular events: insights from the Framingham Heart Study. Eur Radiol. 2019 Nov; 29(11):6140-6148.
Score: 0.051
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.