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Connection

Samuel G. Armato to Diagnosis, Computer-Assisted

This is a "connection" page, showing publications Samuel G. Armato has written about Diagnosis, Computer-Assisted.
  1. The Lung Image Database Consortium (LIDC): ensuring the integrity of expert-defined "truth". Acad Radiol. 2007 Dec; 14(12):1455-63.
    View in: PubMed
    Score: 0.254
  2. Computerized analysis of mesothelioma on CT scans. Lung Cancer. 2005 Jul; 49 Suppl 1:S41-4.
    View in: PubMed
    Score: 0.212
  3. Evaluation of automated lung nodule detection on low-dose computed tomography scans from a lung cancer screening program(1). Acad Radiol. 2005 Mar; 12(3):337-46.
    View in: PubMed
    Score: 0.210
  4. Lung image database consortium: developing a resource for the medical imaging research community. Radiology. 2004 Sep; 232(3):739-48.
    View in: PubMed
    Score: 0.203
  5. Image annotation for conveying automated lung nodule detection results to radiologists. Acad Radiol. 2003 Sep; 10(9):1000-7.
    View in: PubMed
    Score: 0.190
  6. AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging. Med Phys. 2023 Feb; 50(2):e1-e24.
    View in: PubMed
    Score: 0.181
  7. Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program. Radiology. 2002 Dec; 225(3):685-92.
    View in: PubMed
    Score: 0.180
  8. Evaluation of computer-aided detection and diagnosis systems. Med Phys. 2013 Aug; 40(8):087001.
    View in: PubMed
    Score: 0.094
  9. Quality assurance and training procedures for computer-aided detection and diagnosis systems in clinical use. Med Phys. 2013 Jul; 40(7):077001.
    View in: PubMed
    Score: 0.094
  10. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys. 2011 Feb; 38(2):915-31.
    View in: PubMed
    Score: 0.079
  11. The Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) project: a resource for the development of change-analysis software. Clin Pharmacol Ther. 2008 Oct; 84(4):448-56.
    View in: PubMed
    Score: 0.067
  12. Current state and future directions of pleural mesothelioma imaging. Lung Cancer. 2008 Mar; 59(3):411-20.
    View in: PubMed
    Score: 0.064
  13. The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation. Acad Radiol. 2007 Dec; 14(12):1464-74.
    View in: PubMed
    Score: 0.064
  14. The Lung Image Database Consortium (LIDC): a comparison of different size metrics for pulmonary nodule measurements. Acad Radiol. 2007 Dec; 14(12):1475-85.
    View in: PubMed
    Score: 0.064
  15. Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium. Acad Radiol. 2004 Apr; 11(4):462-75.
    View in: PubMed
    Score: 0.049
  16. Best Practices for Artificial Intelligence and Machine Learning for Computer-Aided Diagnosis in Medical Imaging. J Am Coll Radiol. 2024 Feb; 21(2):341-343.
    View in: PubMed
    Score: 0.048
  17. Computerized detection of pulmonary nodules on CT scans. Radiographics. 1999 Sep-Oct; 19(5):1303-11.
    View in: PubMed
    Score: 0.036
  18. Computerized analysis of abnormal asymmetry in digital chest radiographs: evaluation of potential utility. J Digit Imaging. 1999 Feb; 12(1):34-42.
    View in: PubMed
    Score: 0.034
  19. Computerized delineation and analysis of costophrenic angles in digital chest radiographs. Acad Radiol. 1998 May; 5(5):329-35.
    View in: PubMed
    Score: 0.033
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.