AN AI-ENABLED WEIGHTED PRIORITY SCHEDULING ALGORITHM FOR REAL-TIME TELEMEDICINE TRIAGE USING IOMT DATA

One of the widely developing technologies is the Telemedicine which is accepted by all the categories of the disease patient. Providing the treatment on time will safeguard human life; to improve telemedicine consultation, several technological algorithms were added with the consultation assignment between the doctor and patient based on the Human Health Criticality Score. Even though this algorithm has produced better performance, there is still a need to improve the algorithm to produce more efficiency. Especially in the critical scenario like Emergency field, by understanding the patient's emergency condition and assigning the priority to the consultation can safeguard the lifetime of the patient. This article proposed a solution for the critical patient timely teleconsultation support. This research article proposed an algorithm named Enhanced Artificial Intelligent Priority-Based Telemedicine Algorithm (E-AIPTA), that algorithm automatically assigned the priority to the teleconsultation patient based on the real time physiological data. There are five primary body parameters are taken for assigning the priority named as heart rate (HR), oxygen saturation (SpO₂), blood pressure (BP), respiratory rate (RR), and body temperature (T) which are collected with the support of wearable sensor device attached with the patient. All these five parameters are assigned the medical parameter weight of low, medium, high, over-all Health Criticality Score (HCS) is computed to predict the emergency care patient. The proposed algorithm was evaluated using the simulated data sets and results were achieved over 93 % of accuracy, and average computation time is 0.84 seconds. The proposed work shows that it reduces latency and false alarm. This work can improve real time emergency management in critical illness people in teleconsultation.