 Connection
Mark Steele to Machine Learning
This is a "connection" page, showing publications Mark Steele has written about Machine Learning.
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Connection Strength |
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0.458 |
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Raghu G, Flaherty KR, Lederer DJ, Lynch DA, Colby TV, Myers JL, Groshong SD, Larsen BT, Chung JH, Steele MP, Benzaquen S, Calero K, Case AH, Criner GJ, Nathan SD, Rai NS, Ramaswamy M, Hagmeyer L, Davis JR, Gauhar UA, Pankratz DG, Choi Y, Huang J, Walsh PS, Neville H, Lofaro LR, Barth NM, Kennedy GC, Brown KK, Martinez FJ. Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study. Lancet Respir Med. 2019 06; 7(6):487-496.
Score: 0.128
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Kennedy GC, Barth NM, Walsh PS, Huang J, Pankratz DG, Choi Y, Fedorowicz GM, Anderson JD, Raghu G, Martinez FJ, Colby TV, Lynch DA, Brown KK, Groshong SD, Myers JL, Flaherty KR, Steele MP. Reply: Improving Care for Patients with Interstitial Lung Disease, Using Machine Learning, Requires Transparency and Reproducibility. Ann Am Thorac Soc. 2017 12; 14(12):1864-1865.
Score: 0.117
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Pankratz DG, Choi Y, Imtiaz U, Fedorowicz GM, Anderson JD, Colby TV, Myers JL, Lynch DA, Brown KK, Flaherty KR, Steele MP, Groshong SD, Raghu G, Barth NM, Walsh PS, Huang J, Kennedy GC, Martinez FJ. Usual Interstitial Pneumonia Can Be Detected in Transbronchial Biopsies Using Machine Learning. Ann Am Thorac Soc. 2017 Nov; 14(11):1646-1654.
Score: 0.116
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Kim SY, Diggans J, Pankratz D, Huang J, Pagan M, Sindy N, Tom E, Anderson J, Choi Y, Lynch DA, Steele MP, Flaherty KR, Brown KK, Farah H, Bukstein MJ, Pardo A, Selman M, Wolters PJ, Nathan SD, Colby TV, Myers JL, Katzenstein AL, Raghu G, Kennedy GC. Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data. Lancet Respir Med. 2015 Jun; 3(6):473-82.
Score: 0.098
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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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