Footnotes

1. Freedman, M.T., Lo, S.-C., Siebel, J.C., & Bromley, C.M. (2011). Lung Nodules: Improved Detection with Software That Suppresses the Rib and Clavicle on Chest Radiographs. Radiology, 260(1), 265-273. Doi: 10.1148/radiol.11100153.

2. Lo, S. B., Freedman, M. T., Gillis, L. B., White, C. S., & Mun, S. K. (2018). JOURNAL CLUB: Computer-Aided Detection of Lung Nodules on CT With a Computerized Pulmonary Vessel Suppressed Function. American Journal of Roentgenology, 210(3), 480–488. doi: 10.2214/ajr.17.18718.

3. Spieler, B & Baum, N., (2021) Burnout: A Mindful Framework for the Radiologist. Current Problems in Diagnostic Radiology. doi.org/10.1067/j.cpradiol.2021.08.005.

4. Kim YW, Mansfield LT. Fool Me Twice: Delayed Diagnoses in Radiology With Emphasis on Perpetuated Errors. American Journal of Roentgenology. 2014;202(3):465-470. doi:10.2214/ajr.13.11493. 

5. White CS, Salis AI, Meyer CA. Missed Lung Cancer on Chest Radiography and Computed Tomography. Journal of Thoracic Imaging. 1999;14(1):63-68. doi:10.1097/00005382-199901000-00006.

6. Riverain Technologies ClearRead +Confirm FDA 510(k) Reader Study Results, 2012.

7. Performance of a Next Generation Computer-Aided Detection Algorithm for the detection of overlooked lung cancers on Chest Radiographs. RSNA 2013. Gilkeson, Robert C., Frolkis, Calen.

8. Riverain Medical DeltaView FDA 510(K) Reader Study Results 2011.

9. National Research Council (US) Panel on a Research Agenda and New Data for an Aging World. Preparing for an Aging World: The Case for Cross-National Research. Washington (DC): National Academies Press (US); 2001. 6, The Health of Aging Populations. 

10. https://www.lung.org/

11. FDA Clinical Performance Testing Summary, FDA 510k No. K213566.