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Connection

Junji Shiraishi to ROC Curve

This is a "connection" page, showing publications Junji Shiraishi has written about ROC Curve.
Connection Strength

3.698
  1. Charles Edgar Metz, Ph.D. (1942-2012): pioneer in receiver operating characteristic (ROC) analysis. Radiol Phys Technol. 2019 Mar; 12(1):1-5.
    View in: PubMed
    Score: 0.533
  2. Verification of modified receiver-operating characteristic software using simulated rating data. Radiol Phys Technol. 2018 Dec; 11(4):406-414.
    View in: PubMed
    Score: 0.518
  3. Quantification of hazard prediction ability at hazard prediction training (Kiken-Yochi Training: KYT) by free-response receiver-operating characteristic (FROC) analysis. Radiol Phys Technol. 2017 Mar; 10(1):106-112.
    View in: PubMed
    Score: 0.454
  4. Basic concepts and development of an all-purpose computer interface for ROC/FROC observer study. Radiol Phys Technol. 2013 Jan; 6(1):35-41.
    View in: PubMed
    Score: 0.336
  5. [Effect of signal selection in receiver operating characteristics (ROC) analysis]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2010 Nov 20; 66(11):1467-73.
    View in: PubMed
    Score: 0.301
  6. Experimental design and data analysis in receiver operating characteristic studies: lessons learned from reports in radiology from 1997 to 2006. Radiology. 2009 Dec; 253(3):822-30.
    View in: PubMed
    Score: 0.279
  7. [A test method for assessing statistical significance for differences between modalities using multi-reader multi-case ROC analysis]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2007 Oct 20; 63(10):1200-7.
    View in: PubMed
    Score: 0.243
  8. Improved detection of cholesterol gallstones using quasi-material decomposition images generated from single-energy computed tomography images via deep learning. Radiol Phys Technol. 2024 Jun; 17(2):360-366.
    View in: PubMed
    Score: 0.188
  9. [Judgment of the efficacy of digital image diagnosis and ROC analysis]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2002 Jan; 58(1):14-19.
    View in: PubMed
    Score: 0.162
  10. [Investigation of Clinical Utility of Radiological Technologist's Reading Report as a Second Opinion for Medical Doctor Reading of Digital Mammogram]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2020; 76(10):997-1008.
    View in: PubMed
    Score: 0.141
  11. [Development of a computer-aided diagnosis system for the distinction between benign and malignant gastric lesions]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2012; 68(11):1474-85.
    View in: PubMed
    Score: 0.081
  12. Observer study for evaluating potential utility of a super-high-resolution LCD in the detection of clustered microcalcifications on digital mammograms. J Digit Imaging. 2010 Apr; 23(2):161-9.
    View in: PubMed
    Score: 0.067
  13. Usefulness of temporal subtraction images for identification of interval changes in successive whole-body bone scans: JAFROC analysis of radiologists' performance. Acad Radiol. 2007 Aug; 14(8):959-66.
    View in: PubMed
    Score: 0.060
  14. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance. Acad Radiol. 2006 Aug; 13(8):995-1003.
    View in: PubMed
    Score: 0.056
  15. Computer-aided diagnosis to distinguish benign from malignant solitary pulmonary nodules on radiographs: ROC analysis of radiologists' performance--initial experience. Radiology. 2003 May; 227(2):469-74.
    View in: PubMed
    Score: 0.045
  16. Computer-aided diagnosis for estimating the malignancy grade of hepatocellular carcinoma using contrast-enhanced ultrasound: an ROC observer study. Liver Int. 2016 07; 36(7):1026-32.
    View in: PubMed
    Score: 0.027
  17. Improved detection of subtle lung nodules by use of chest radiographs with bone suppression imaging: receiver operating characteristic analysis with and without localization. AJR Am J Roentgenol. 2011 May; 196(5):W535-41.
    View in: PubMed
    Score: 0.019
  18. [ROC analysis for evaluating the detectability of image unsharpness due to the patient's movement: phantom study comparing preview and diagnostic LCDs]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2011; 67(7):772-8.
    View in: PubMed
    Score: 0.019
  19. Presentation of similar images as a reference for distinction between benign and malignant masses on mammograms: analysis of initial observer study. J Digit Imaging. 2010 Oct; 23(5):592-602.
    View in: PubMed
    Score: 0.018
  20. Potential usefulness of similar images in the differential diagnosis of clustered microcalcifications on mammograms. Radiology. 2009 Dec; 253(3):625-31.
    View in: PubMed
    Score: 0.017
  21. Improved detection of hepatic metastases with contrast-enhanced low mechanical-index pulse inversion ultrasonography during the liver-specific phase of sonazoid: observer performance study with JAFROC analysis. Acad Radiol. 2009 Jul; 16(7):798-809.
    View in: PubMed
    Score: 0.017
  22. Computer-aided detection in computed tomography colonography: current status and problems with detection of early colorectal cancer. Radiat Med. 2008 Jun; 26(5):261-9.
    View in: PubMed
    Score: 0.016
  23. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization. Radiology. 2005 Nov; 237(2):684-90.
    View in: PubMed
    Score: 0.013
  24. Effect of temporal subtraction images on radiologists' detection of lung cancer on CT: results of the observer performance study with use of film computed tomography images. Acad Radiol. 2004 Dec; 11(12):1337-43.
    View in: PubMed
    Score: 0.012
  25. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol. 2004 Nov; 183(5):1209-15.
    View in: PubMed
    Score: 0.012
  26. Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases. Acad Radiol. 2004 Jan; 11(1):29-37.
    View in: PubMed
    Score: 0.012
  27. Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules. Med Phys. 2003 Oct; 30(10):2584-93.
    View in: PubMed
    Score: 0.011
  28. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys. 2003 Sep; 30(9):2440-54.
    View in: PubMed
    Score: 0.011
  29. Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies. Radiographics. 2003 Jan-Feb; 23(1):255-65.
    View in: PubMed
    Score: 0.011
  30. [Development of an image processing scheme for chest radiographs using a dot printer]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2002 Sep; 58(9):1268-77.
    View in: PubMed
    Score: 0.011
  31. Digital chest radiography: effect of temporal subtraction images on detection accuracy. Radiology. 1997 Feb; 202(2):447-52.
    View in: PubMed
    Score: 0.007
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.