Explore how Aidoc’s clinical AI solutions can increase hospital efficiency, show proven return on investment, and help enable better outcomes.
Learn moreImproving the lives of patients across the care continuum
Setting the standard for neuro care with real time notification
Automatically analyze imaging to rapidly identify abnormalities
Discover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
Learn moreAidoc’s proprietary enterprise platform to reliably deploy, measure and run AI at scale
Alerts the right users across the imaging and clinical workflow expediting decision-making
Custom configured and integrated into existing systems with minimal effort from IT teams
Vetted third-party algorithm developers and OEMs for the industry’s most complete platform
See the latest research, case studies, tips and more to start improving outcomes with healthcare AI today.
Learn moreLearn more about Aidoc’s approach, mission and leadership team that is revolutionizing healthcare with AI.
Learn moreExplore how Aidoc’s clinical AI solutions can increase hospital efficiency, show proven return on investment, and help enable better outcomes.
Learn moreImproving the lives of patients across the care continuum
Setting the standard for neuro care with real time notification
Automatically analyze imaging to rapidly identify abnormalities
Discover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
Learn moreAidoc’s proprietary enterprise platform to reliably deploy, measure and run AI at scale
Alerts the right users across the imaging and clinical workflow expediting decision-making
Custom configured and integrated into existing systems with minimal effort from IT teams
Vetted third-party algorithm developers and OEMs for the industry’s most complete platform
See the latest research, case studies, tips and more to start improving outcomes with healthcare AI today.
Learn moreLearn more about Aidoc’s approach, mission and leadership team that is revolutionizing healthcare with AI.
Learn moreMaterials & Methods
A retrospective cohort study assessing the prevalence of reported and unreported incidental pulmonary embolism (iPE) in patients with cancer. were identified through automatic detection with an AI algorithm. All patients with cancer with an elective CT (chest and/or abdo) study, including the chest, between July 1, 2018 to June 30, 2019 were included and study reports and images were reviewed and processed by the AI algorithm.
Results
1,892 CT studies were included. Per study, iPE was present in 4.0% of the oncology population. 80% miss rate (53/65) showed a >400% enhanced detection rate by AI (53/12). Of those 58% (31/53) of the misses where lobar or segmental and 59% (13/22) of the subsegmental findings involved multiple vessels (i.e.: higher clinical significance than a solitary sub-seg finding). The sensitivity 90.7%, specificity 99.8%, PPV 95.6%, NPV 99.6%.
Conclusions
In a retrospective single-center study on patients with cancer, unreported iPE were common, with the majority lying proximal to the subsegmental arteries. The evaluated AI algorithm had very high sensitivity and specificity, so it has the potential to increase the detection rate of iPE.
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