 Connection
Stephen Humphries to Retrospective Studies
This is a "connection" page, showing publications Stephen Humphries has written about Retrospective Studies.
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Connection Strength |
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0.326 |
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Oh AS, Lynch DA, Swigris JJ, Baraghoshi D, Dyer DS, Hale VA, Koelsch TL, Marrocchio C, Parker KN, Teague SD, Flaherty KR, Humphries SM. Deep Learning-based Fibrosis Extent on Computed Tomography Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed Computed Tomography Pattern. Ann Am Thorac Soc. 2024 02; 21(2):218-227.
Score: 0.056
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Humphries SM, Mackintosh JA, Jo HE, Walsh SLF, Silva M, Calandriello L, Chapman S, Ellis S, Glaspole I, Goh N, Grainge C, Hopkins PMA, Keir GJ, Moodley Y, Reynolds PN, Walters EH, Baraghoshi D, Wells AU, Lynch DA, Corte TJ. Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis. Respirology. 2022 12; 27(12):1045-1053.
Score: 0.050
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Humphries SM, Notary AM, Centeno JP, Strand MJ, Crapo JD, Silverman EK, Lynch DA. Deep Learning Enables Automatic Classification of Emphysema Pattern at CT. Radiology. 2020 02; 294(2):434-444.
Score: 0.042
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Humphries SM, Swigris JJ, Brown KK, Strand M, Gong Q, Sundy JS, Raghu G, Schwarz MI, Flaherty KR, Sood R, O'Riordan TG, Lynch DA. Quantitative high-resolution computed tomography fibrosis score: performance characteristics in idiopathic pulmonary fibrosis. Eur Respir J. 2018 09; 52(3).
Score: 0.039
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Humphries SM, Yagihashi K, Huckleberry J, Rho BH, Schroeder JD, Strand M, Schwarz MI, Flaherty KR, Kazerooni EA, van Beek EJR, Lynch DA. Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up. Radiology. 2017 10; 285(1):270-278.
Score: 0.035
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Sotoudeh-Paima S, Lynch DA, Humphries SM, Samei E, Abadi E. Precise Lung Density Quantification with a Physics-based CT Harmonizer. Radiol Cardiothorac Imaging. 2026 Apr; 8(2):e250124.
Score: 0.016
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Mackintosh JA, Walsh SLF, Silva M, Calandriello L, Humphries SM, Lynch DA, Jo HE, Glaspole I, Grainge C, Goh N, Hopkins PMA, Moodley Y, Reynolds PN, Zappala C, Keir G, Cooper WA, Mahar AM, Ellis S, Wells AU, Corte TJ. Likelihood of Usual Interstitial Pneumonia: A Novel Approach to Prognosis for Pulmonary Fibrosis. Respirology. 2026 05; 31(5):521-529.
Score: 0.016
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Marrocchio C, Humphries SM, Lynch DA. Chest Computed Tomography Findings in Unilateral Pulmonary Fibrosis Secondary to Chronic Hypoperfusion. J Thorac Imaging. 2024 Sep 01; 39(5):269-274.
Score: 0.014
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Walsh SLF, Mackintosh JA, Calandriello L, Silva M, Sverzellati N, Larici AR, Humphries SM, Lynch DA, Jo HE, Glaspole I, Grainge C, Goh N, Hopkins PMA, Moodley Y, Reynolds PN, Zappala C, Keir G, Cooper WA, Mahar AM, Ellis S, Wells AU, Corte TJ. Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography. Am J Respir Crit Care Med. 2022 10 01; 206(7):883-891.
Score: 0.013
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DeBoer EM, Liptzin DR, Humphries SM, Lynch DA, Robison K, Galambos C, Dishop MK, Deterding RR, Weinman JP. Ground glass and fibrotic change in children with surfactant protein C dysfunction mutations. Pediatr Pulmonol. 2021 07; 56(7):2223-2231.
Score: 0.012
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Walsh SLF, Humphries SM, Wells AU, Brown KK. Imaging research in fibrotic lung disease; applying deep learning to unsolved problems. Lancet Respir Med. 2020 11; 8(11):1144-1153.
Score: 0.011
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Raghu G, Ley B, Brown KK, Cottin V, Gibson KF, Kaner RJ, Lederer DJ, Noble PW, Song JW, Wells AU, Whelan TP, Lynch DA, Humphries SM, Moreau E, Goodman K, Patterson SD, Smith V, Gong Q, Sundy JS, O'Riordan TG, Martinez FJ. Risk factors for disease progression in idiopathic pulmonary fibrosis. Thorax. 2020 01; 75(1):78-80.
Score: 0.010
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Mastej EJ, DeBoer EM, Humphries SM, Cook MC, Hunter KS, Liptzin DR, Weinman JP, Deterding RR. Lung and airway shape in neuroendocrine cell hyperplasia of infancy. Pediatr Radiol. 2018 11; 48(12):1745-1754.
Score: 0.009
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Christensen AM, Humphries SM, Goh KY, Swift D. Advanced "tactile" medical imaging for separation surgeries of conjoined twins. Childs Nerv Syst. 2004 Aug; 20(8-9):547-53.
Score: 0.004
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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