Explore how Aidoc’s clinical AI solutions can increase hospital efficiency, show proven return on investment, and help enable better outcomes.
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Consistently measure disease and capture incidental findings
Setting the standard for neuro care with real time notification
Streamline workflows and centralize patient management
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.
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Connect the right users across workflows
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Vetted third-party algorithm developers and OEMs
Information and resources about AI transformation rooted in real-world experiences.
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Learn 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 morePrioritize findings and activate care teams in streamlined workflows
Consistently measure disease and capture incidental findings
Setting the standard for neuro care with real time notification
Streamline workflows and centralize patient management
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
Connect the right users across workflows
Ensure patients are identified, captured and followed
Custom configuration with minimal IT lift
Vetted third-party algorithm developers and OEMs
Information and resources about AI transformation rooted in real-world experiences.
Learn MoreLearn how to go beyond the algorithm to develop a scalable AI strategy and implementation plan.
Learn more about Aidoc’s approach, mission and leadership team that is revolutionizing healthcare with AI.
Learn moreiPE algorithm was applied retrospectively to 2793 consecutive patients undergoing Chest CT between 05/2020 to 01/2021 and compared to the original radiology report. Concordant cases between the original report and AI were considered ground truth. Discordant cases deemed positive by AI and negative by the report were reassessed by the Radiologist.
iPE prevelance was 2.3% (65/2792). 45 cases were positive by both AI and radiologist report and AI detected 23 additional discordant positive cases.87% (20/23) were considered TP on secondary review. The AI enhanced detection rate was 44.4% (20/45). 10% (2/20) were chronic PE, 90% (18/20) were acute/subacute PE. 70% (14/20) were subsegmental PE. 40% (8/20) had follow-up imaging: In 50% (4/8) cases iPE was not resolved. In 38% (3/8) patients iPE was noticed on follow-up and reported. In all 3, anticoagulation therapy was initiated. The average treatment delay was 132 days. In 35% (3/20) discrepant anticoagulation was given for other reasons. In the remaining 65% (13/20) cases, iPE was unnoticed by the radiologist or clinician and the patient did not receive any treatment. 25% (5/20) patients died of unrelated causes.
The improved detection rate of iPE by AI may bring significant benefits for prompt management in selected individuals, especially the ones at risk for recurrent thromboembolic events.
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