Artificial Swarm Intelligence employed to Amplify Diagnostic Accuracy in Radiology

Louis Rosenberg, Matthew Lungren, Safwan Halabi, Gregg Willcox, David Baltaxe, Mimi Lyons

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Scopus citations

Abstract

Swarm Intelligence (SI) is a biological phenomenon in which groups of organisms amplify their combined brainpower by forming real-time systems. It has been studied for decades in fish schools, bird flocks, and bee swarms. Recent advances in networking and AI technologies have enabled distributed human groups to form closed-loop systems modeled after natural swarms. The process is referred to as Artificial Swarm Intelligence (ASI) and has been shown to significantly amplify group performance. The present research applies ASI technology to the field of medicine, exploring if small groups of networked radiologists can improve their diagnostic accuracy when reviewing chest X-rays for the presence of pneumonia. Performance data was collected for individual radiologists generating diagnoses alone, as well as for small groups of radiologists working together to generate diagnoses as a real-time ASI system. Diagnoses were also collected from a state-of-the-art deep learning system (CheXNet) developed at Stanford University. Results showed that small groups of networked radiologists, when working as a real-time ASI system, were significantly more accurate than the individual radiologists on their own, reducing diagnostic errors by 33%. Results also showed that small groups of networked radiologists, when working as an ASI system, were significantly more accurate (22%) than a state-of-the-art deep learning system (CheXNet).

Original languageEnglish (US)
Title of host publication2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2018
EditorsSatyajit Chakrabarti, Himadri Nath Saha
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1186-1191
Number of pages6
ISBN (Electronic)9781538672662
DOIs
StatePublished - Jul 2 2018
Event9th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2018 - Vancouver, Canada
Duration: Nov 1 2018Nov 3 2018

Publication series

Name2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2018

Conference

Conference9th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2018
Country/TerritoryCanada
CityVancouver
Period11/1/1811/3/18

Keywords

  • AI
  • Artificial Intelligence
  • Collective Intelligence
  • Diagnostic Radiology
  • Human Swarming
  • Swarm Intelligence

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Instrumentation

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