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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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 moreA total of 1,936 consecutive non-contrast head CT scans from two CT scanners used for inpatient and emergency room patients at a large academic hospital were prospectively acquired over a time period of 47 consecutive days. Study turnaround time (TAT) was measured automatically as the time difference between study completion time (=study accessible to radiologists for reporting) to study reporting time (=first report visible to clinicians, regardless of whether preliminary or final).
A total of 381 ICH-AI+ cases were found, of which 190 cases were flagged. TATs for flagged cases (52 ± 25 min.) were significantly lower than TATs for non-flagged (82 ± 31 min.) cases (p<0.05, Wilcoxon signed-rank test).
Notifying radiologists on automatically detected ICH statistically significantly reduces TAT for reporting ICH to clinicians in emergency setting. Reduced TAT may expedite clinically indicated therapeutic interventions.
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