Explore how Aidoc’s clinical AI solutions can increase hospital efficiency, show proven return on investment, and help enable better outcomes.
Learn moreDiscover 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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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 moreDiscover 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 moreSee 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 moreAs part of the QA protocol, a team of four radiologists and a PACS administrator was formed. All positive cases detected by AI during a four-month period from Dec. 2019 to March 2020 were compared with a radiologists’ report for discordant results. Studies with discordant results were reviewed by the radiologists on the QA team daily; email notifications were sent to the radiologist who interpreted the study as well as to the QA team and true positive cases were addended.
335 CT scans were detected by AI as positive for PE. Retrospective review confirmed 236 cases as true positives (PPV = 70%). 220 cases were correctly interpreted as positive for PE by the radiologists. 16 cases were overlooked despite being correctly identified by AI. 11 cases were due to human error (notification overlooked) and five cases were due to technical errors (notification was late/not received). All 16 cases were reviewed by the QA team and communicated to the referring providers within 12 hours.
6.8% (16 out of 236) of PE cases were overlooked by the radiologists. Creating a multifaceted QA approach with the addition of AI can help avoid missing critical findings and prevent adverse clinical outcomes.
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