Mohammed Dalwai, an emergency clinician working with Doctors with borders describes one of his experiences:

It was in Pakistan in 2011, on my first assignment, that I saw patients dying due to incorrect triaging. One day, I lost a patient. A young woman, 22 years old, came in with abdominal pain. She was incorrectly triaged, and she waited for eight hours. She died — and it really affected me. She was a woman, she was sidelined, she was put in a corner — no one cared, no one did the triage properly. If she’d been triaged correctly, we would have realized she was pregnant, and we would have prioritized her.

Clinical Need for Intelligent Triage System

Stakeholders

Patients and Doctors in overcrowded situations

Lesser Trained Nurses and Hospital Staff

Hospital Administration looking for better outcomes and management

Government who can monitor such data and be proactive to contain disease spread.

Technology behind Medi-Assess

The system inputs triage data based on the One-Two Triage Protocol and output a triage level. The collected data is further used as input features for our deep learning model trained on the NHAMCS dataset to predict emergency outcomes. Using the emergency outcome we calculate the survival probability of the patient in the emergency which is used by the clinician for resource allocation. To understand more about the tech-stack, refer to the Research page.

News

[08/02/2021] Research idea presented at Workshop on Health Intelligence, AAAI, 2021.

[15/12/2020] Research Paper accepted for a print in Springer book volume in the “Studies in Computational Intelligence” series.

[18/06/2020] Research idea presented at Engineering in Medicine and Biology Conference (EMBC), 2020.

[20/04/2020] Awarded the second-runner up position at Johns Hopkins International Healthcare Design Competition.