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.
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 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 moreAn ML algorithm was incorporated across CT scanners at imaging sites in January 2018. RTAT and LOS were derived for reports and patients between July 2017 and December 2017 prior to implementation of ML and compared to those between January 2018 and June 2018 after implementation of ML. A total of 25,658 and 24,996 ED and inpatient cases were evaluated across the entire healthcare system before and after ML, respectively.
Inpatient LOS for positive cases decreased from 6.91 days to 6.16 days (p>.05). ED LOS decreased by 59.10 minutes, from 566.56 minutes to 507.56 minutes (p<.001).
The clinical application of AI platform for the detection of ICH significantly decreased LOS, indicating that patients were efficiently triaged to the appropriate care.
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