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Connection

David Lynch to Sensitivity and Specificity

This is a "connection" page, showing publications David Lynch has written about Sensitivity and Specificity.

 
Connection Strength
 
 
 
0.970
 
  1. Nambu A, Zach J, Schroeder J, Jin GY, Kim SS, Kim YI, Schnell C, Bowler R, Lynch DA. Relationships between diffusing capacity for carbon monoxide (DLCO), and quantitative computed tomography measurements and visual assessment for chronic obstructive pulmonary disease. Eur J Radiol. 2015 May; 84(5):980-5.
    View in: PubMed
    Score: 0.091
  2. Deutsch EC, Oglesbee D, Greeley NR, Lynch DR. Usefulness of frataxin immunoassays for the diagnosis of Friedreich ataxia. J Neurol Neurosurg Psychiatry. 2014 Sep; 85(9):994-1002.
    View in: PubMed
    Score: 0.085
  3. Chung JH, Little BP, Forssen AV, Yong J, Nambu A, Kazlouski D, Puderbach M, Biederer J, Lynch DA. Proton MRI in the evaluation of pulmonary sarcoidosis: comparison to chest CT. Eur J Radiol. 2013 Dec; 82(12):2378-85.
    View in: PubMed
    Score: 0.083
  4. St John Sutton M, Ky B, Regner SR, Schadt K, Plappert T, He J, D'Souza B, Lynch DR. Longitudinal strain in Friedreich Ataxia: a potential marker for early left ventricular dysfunction. Echocardiography. 2014; 31(1):50-7.
    View in: PubMed
    Score: 0.082
  5. Deutsch EC, Santani AB, Perlman SL, Farmer JM, Stolle CA, Marusich MF, Lynch DR. A rapid, noninvasive immunoassay for frataxin: utility in assessment of Friedreich ataxia. Mol Genet Metab. 2010 Oct-Nov; 101(2-3):238-45.
    View in: PubMed
    Score: 0.067
  6. Hwang JH, Misumi S, Sahin H, Brown KK, Newell JD, Lynch DA. Computed tomographic features of idiopathic fibrosing interstitial pneumonia: comparison with pulmonary fibrosis related to collagen vascular disease. J Comput Assist Tomogr. 2009 May-Jun; 33(3):410-5.
    View in: PubMed
    Score: 0.061
  7. Lynch DA. Quantitative CT of fibrotic interstitial lung disease. Chest. 2007 Mar; 131(3):643-644.
    View in: PubMed
    Score: 0.053
  8. Lynch DR, Mozley PD, Sokol S, Maas NM, Balcer LJ, Siderowf AD. Lack of effect of polymorphisms in dopamine metabolism related genes on imaging of TRODAT-1 in striatum of asymptomatic volunteers and patients with Parkinson's disease. Mov Disord. 2003 Jul; 18(7):804-12.
    View in: PubMed
    Score: 0.041
  9. Richeldi L, Scholand MB, Lynch DA, Colby TV, Myers JL, Groshong SD, Chung JH, Benzaquen S, Nathan SD, Davis JR, Schmidt SL, Hagmeyer L, Sonetti D, Hetzel J, Criner GJ, Case AH, Ramaswamy M, Calero K, Gauhar UA, Patel NM, Lancaster L, Choi Y, Pankratz DG, Walsh PS, Lofaro LR, Huang J, Bhorade SM, Kennedy GC, Martinez FJ, Raghu G. Utility of a Molecular Classifier as a Complement to High-Resolution Computed Tomography to Identify Usual Interstitial Pneumonia. Am J Respir Crit Care Med. 2021 01 15; 203(2):211-220.
    View in: PubMed
    Score: 0.035
  10. Fleming H, Clifford SM, Haughey A, MacDermott R, McVeigh N, Healy GM, Lavelle L, Abbara S, Murphy DJ, Fabre A, McKone E, McCarthy C, Butler M, Doran P, Lynch DA, Keane MP, Dodd JD. Differentiating combined pulmonary fibrosis and emphysema from pure emphysema: utility of late gadolinium-enhanced MRI. Eur Radiol Exp. 2020 11 03; 4(1):61.
    View in: PubMed
    Score: 0.034
  11. Kuperus JS, Oudkerk SF, Foppen W, Mohamed Hoesein FA, Gielis WP, Waalwijk J, Regan EA, Lynch DA, Oner FC, de Jong PA, Verlaan JJ. Criteria for Early-Phase Diffuse Idiopathic Skeletal Hyperostosis: Development and Validation. Radiology. 2019 05; 291(2):420-426.
    View in: PubMed
    Score: 0.031
  12. 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.
    View in: PubMed
    Score: 0.031
  13. Choi Y, Liu TT, Pankratz DG, Colby TV, Barth NM, Lynch DA, Walsh PS, Raghu G, Kennedy GC, Huang J. Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions. BMC Genomics. 2018 May 09; 19(Suppl 2):101.
    View in: PubMed
    Score: 0.029
  14. Guo L, Wang Q, Weng L, Hauser LA, Strawser CJ, Rocha AG, Dancis A, Mesaros C, Lynch DR, Blair IA. Liquid Chromatography-High Resolution Mass Spectrometry Analysis of Platelet Frataxin as a Protein Biomarker for the Rare Disease Friedreich's Ataxia. Anal Chem. 2018 02 06; 90(3):2216-2223.
    View in: PubMed
    Score: 0.028
  15. Chung JH, Cox CW, Montner SM, Adegunsoye A, Oldham JM, Husain AN, Vij R, Noth I, Lynch DA, Strek ME. CT Features of the Usual Interstitial Pneumonia Pattern: Differentiating Connective Tissue Disease-Associated Interstitial Lung Disease From Idiopathic Pulmonary Fibrosis. AJR Am J Roentgenol. 2018 Feb; 210(2):307-313.
    View in: PubMed
    Score: 0.028
  16. 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.
    View in: PubMed
    Score: 0.028
  17. Ash SY, Harmouche R, Ross JC, Diaz AA, Hunninghake GM, Putman RK, Onieva J, Martinez FJ, Choi AM, Lynch DA, Hatabu H, Rosas IO, Estepar RSJ, Washko GR. The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers. Acad Radiol. 2017 08; 24(8):941-946.
    View in: PubMed
    Score: 0.026
  18. 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.
    View in: PubMed
    Score: 0.023
  19. Bhatt SP, Kim YI, Wells JM, Bailey WC, Ramsdell JW, Foreman MG, Jensen RL, Stinson DS, Wilson CG, Lynch DA, Make BJ, Dransfield MT. FEV(1)/FEV(6) to diagnose airflow obstruction. Comparisons with computed tomography and morbidity indices. Ann Am Thorac Soc. 2014 Mar; 11(3):335-41.
    View in: PubMed
    Score: 0.021
  20. Hersh CP, Washko GR, Est?par RS, Lutz S, Friedman PJ, Han MK, Hokanson JE, Judy PF, Lynch DA, Make BJ, Marchetti N, Newell JD, Sciurba FC, Crapo JD, Silverman EK. Paired inspiratory-expiratory chest CT scans to assess for small airways disease in COPD. Respir Res. 2013 Apr 08; 14:42.
    View in: PubMed
    Score: 0.020
  21. Watadani T, Sakai F, Johkoh T, Noma S, Akira M, Fujimoto K, Bankier AA, Lee KS, M?ller NL, Song JW, Park JS, Lynch DA, Hansell DM, Remy-Jardin M, Franquet T, Sugiyama Y. Interobserver variability in the CT assessment of honeycombing in the lungs. Radiology. 2013 Mar; 266(3):936-44.
    View in: PubMed
    Score: 0.020
  22. Ginsburg SB, Lynch DA, Bowler RP, Schroeder JD. Automated texture-based quantification of centrilobular nodularity and centrilobular emphysema in chest CT images. Acad Radiol. 2012 Oct; 19(10):1241-51.
    View in: PubMed
    Score: 0.019
  23. Aberle DR, Berg CD, Black WC, Church TR, Fagerstrom RM, Galen B, Gareen IF, Gatsonis C, Goldin J, Gohagan JK, Hillman B, Jaffe C, Kramer BS, Lynch D, Marcus PM, Schnall M, Sullivan DC, Sullivan D, Zylak CJ. The National Lung Screening Trial: overview and study design. Radiology. 2011 Jan; 258(1):243-53.
    View in: PubMed
    Score: 0.017
  24. Washko GR, Lynch DA, Matsuoka S, Ross JC, Umeoka S, Diaz A, Sciurba FC, Hunninghake GM, San Jos? Est?par R, Silverman EK, Rosas IO, Hatabu H. Identification of early interstitial lung disease in smokers from the COPDGene Study. Acad Radiol. 2010 Jan; 17(1):48-53.
    View in: PubMed
    Score: 0.016
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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