Abstract
Twelve radiologists independently diagnosed 74 medical images. We use two approaches to combine their diagnoses: a collective algorithmic strategy and a social consensus strategy using swarm techniques. The algorithmic strategy uses weighted averages and a geometric approach to automatically produce an aggregate diagnosis. The social consensus strategy used visual cues to quickly impart the essence of the diagnoses to the radiologists as they produced an emergent diagnosis. Both strategies provide access to additional useful information from the original diagnoses. The mean number of correct diagnoses from the radiologists was 50 and the best was 60. The algorithmic strategy produced 63 correct diagnoses and the social consensus produced 67. The algorithm’s accuracy in distinguishing normal vs. abnormal patients (0.919) was significantly higher than the radiologists’ mean accuracy (0.861; p = 0.047). The social consensus’ accuracy (0.951; p = 0.007) showed further improvement.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Brutschy, A., Scheidler, A., Merkle, D., Middendorf, M.: Learning from house-hunting ants: collective decision-making in organic computing systems. In: Dorigo, M., Birattari, M., Blum, C., Clerc, M., Stützle, T., Winfield, A.F.T. (eds.) ANTS 2008. LNCS, vol. 5217, pp. 96–107. Springer, Heidelberg (2008)
DeLong, E., DeLong, D., Clarke-Pearson, D.: Comparing the areas under two of more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44, 837–845 (1988)
Drew, T., Vo, M., Wolfe, J.: The invisible gorilla strikes again sustained inattentional blindness in expert observers. Psychological Science 24(9), 1848–1853 (2013)
Obuchowski, N., Goske, M., Applegate, K.: Assessing physicians’ accuracy in diagnosing pediatric patients with acute abdominal pain: measuring accuracy for multiple diseases. Statistics in Medicine 20, 3261–3278 (2001)
Obuchowski, N., Rockette, H.: Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests: an anova approach with dependent observations. Communication in Statistics – Simulation 24, 285–308 (1995)
Surowiecki, J.: The Wisdom of Crowds. Doubleday, New York (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Palmer, D.W., Piraino, D.W., Obuchowski, N.A., Bullen, J.A. (2014). Emergent Diagnoses from a Collective of Radiologists: Algorithmic versus Social Consensus Strategies. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2014. Lecture Notes in Computer Science, vol 8667. Springer, Cham. https://doi.org/10.1007/978-3-319-09952-1_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-09952-1_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09951-4
Online ISBN: 978-3-319-09952-1
eBook Packages: Computer ScienceComputer Science (R0)