P08 : Bits to Bedside: An Ingenious Exploration of Machine Learning in Triage Assessments (Continued...)


Students Zena Alsaadi
Bahaa Alsaadi
School HCDSB - Bishop P. F. Reding Secondary School - Milton
Level Senior 11/12 - Grade 9
Group Group 11 - Engineering and Computing IV
Abstract The purpose of this ingenious project is to utilize machine learning to aid in the long-term crisis of hospital wait times by targeting one aspect of the hospital process at a time (in this case, the triage assessment process in the ER). The innovative application is meant to work alongside real nurses by assessing less urgent patients using the Canadian Triage and Acuity Scale through a user-friendly self-check-in kiosk that utilizes both visual and numerical input data, allowing the wait times of severe and less severe patient cases to reduce by 36% and 10% respectively. In the grand sceheme of the ER experience, any reduction in wait times at each step of the process is vital.
Awards
Group Award Prize
Merit AwardsGold Merit Award$ 100
Canada-Wide Science Fair Trip AwardsCanada-Wide Science Fair Trip Award
Mohawk College Computer Science & Information Technology Excellence AwardsMohawk College Computer Science & Information Technology Excellence Award$ 50
Ola Lunyk-Child Memorial Health AwardsOla Lunyk-Child Memorial Health Science Award - Third$ 100