Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs

Byung C Yoon, Stuart R Pomerantz, Nathaniel D Mercaldo, Swati Goyal, Eric M L’Italien, Michael H Lev, Karen A Buch, Bradley R Buchbinder, John W Chen, John Conklin, Rajiv Gupta, George J Hunter, Shahmir C Kamalian, Hillary R Kelly, Otto Rapalino, Sandra P Rincon, Javier M Romero, Julian He, Pamela W Schaefer, Synho Do and Ramon Gilberto González

PLOS ONE, 2023, vol. 18, issue 3, 1-15

Abstract: Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty into an ML algorithm that detects intracranial hemorrhage or other urgent intracranial abnormalities and evaluated prospectively identified, 1000 consecutive noncontrast head CTs assigned to Emergency Department Neuroradiology for interpretation. The algorithm classified the scans into high (IC+) and low (IC-) probabilities for intracranial hemorrhage or other urgent abnormalities. All other cases were designated as No Prediction (NP) by the algorithm. The positive predictive value for IC+ cases (N = 103) was 0.91 (CI: 0.84–0.96), and the negative predictive value for IC- cases (N = 729) was 0.94 (0.91–0.96). Admission, neurosurgical intervention, and 30-day mortality rates for IC+ was 75% (63–84), 35% (24–47), and 10% (4–20), compared to 43% (40–47), 4% (3–6), and 3% (2–5) for IC-. There were 168 NP cases, of which 32% had intracranial hemorrhage or other urgent abnormalities, 31% had artifacts and postoperative changes, and 29% had no abnormalities. An ML algorithm incorporating uncertainty classified most head CTs into clinically relevant groups with high predictive values and may help accelerate the management of patients with intracranial hemorrhage or other urgent intracranial abnormalities.

Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0281900 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 81900&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0281900

DOI: 10.1371/journal.pone.0281900

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().