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Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels
  1. Pranav Warman1,
  2. Anmol Warman1,
  3. Roshan Warman1,
  4. Andrew Degnan2,3,
  5. Johan Blickman1,
  6. David Smith1,
  7. Paul McHale1,
  8. Zachary Coburn1,
  9. Sean McCormick1,
  10. Varun Chowdhary1,
  11. Dev Dash4,
  12. Rohit Sangal5,
  13. Jason Vadhan6,
  14. Tulio Bueso7,
  15. Thomas Windisch7,8,
  16. Gabriel Neves7
  1. 1 Caire Health, Tampa, Florida, USA
  2. 2 Department of Radiology, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
  3. 3 Lourdes Imaging Associates, Camden, New Jersey, USA
  4. 4 Stanford Medicine, Stanford, California, USA
  5. 5 Yale School of Medicine, New Haven, Connecticut, USA
  6. 6 UTSW, Dallas, Texas, USA
  7. 7 TTUHSC, Lubbock, Texas, USA
  8. 8 Covenant Health, Lubbock, Texas, USA
  1. Correspondence to Dr Gabriel Neves, TTUHSC, Lubbock, TX 79430, USA; Gabeneves1{at}


Background Tools to increase the turnaround speed and accuracy of imaging reports could positively influence ED logistics. The Caire ICH is an artificial intelligence (AI) software developed for ED physicians to recognise intracranial haemorrhages (ICHs) on non-contrast enhanced cranial CT scans to manage the clinical care of these patients in a timelier fashion.

Methods A dataset of 532 non-contrast cranial CT scans was reviewed by five board-certified emergency physicians (EPs) with an average of 14.8 years of practice experience. The scans were labelled in random order for the presence or absence of an ICH. If an ICH was detected, the reader further labelled all subtypes present (ie, epidural, subdural, subarachnoid, intraparenchymal and/or intraventricular haemorrhage). After a washout period, the five EPs reviewed again the scans individually with the assistance of Caire ICH. The mean accuracy of the EP readings with AI assistance was compared with the mean accuracy of three general radiologists reading the films individually. The final diagnosis (ie, ground truth) was adjudicated by a consensus of the radiologists after their individual readings.

Results Mean EP reader accuracy significantly increased by 6.20% (95% CI for the difference 5.10%–7.29%; p=0.0092) when using Caire ICH to detect an ICH. Mean accuracy of the EP cohort in detecting an ICH using Caire ICH was found to be more accurate than the radiologist cohort prior to discussion; this difference, however, was not statistically significant.

Conclusion The Caire ICH software significantly improved the accuracy and sensitivity of detecting an ICH by the EP to a level comparable to general radiologists. Further prospective research with larger numbers will be needed to understand the impact of Caire ICH on ED logistics and patient outcomes.

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Data availability statement

Additional data requests may be made available upon reasonable requests to the corresponding author.

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Data availability statement

Additional data requests may be made available upon reasonable requests to the corresponding author.

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  • Handling editor Alex Novak

  • Contributors PW, AW and RW conceived and designed the research, curated the imaging data and designed the algorithm. AD, JB, DS, PM, ZC, SM and VC provided labels for the data. GN, DD, RS, JV, TB and TW provided clinical oversight and general guidance. GN, PW, AW, and RW are the guarantors of this work. All authors drafted the manuscript and performed key revisions to the manuscript and data presentation. All authors approved the final manuscript.

  • Funding This work was supported by Caire Health (Tampa, Florida, USA).

  • Competing interests AD, JB, DS, PM, ZC, SM and VC received compensation for their involvement with this work. PW, AW and RW are employees of Caire Health.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.