IMPLEMENTATION OF TIME PREDICTION SYSTEM FOR THE PATIENTS IN HOSPITAL USING PARALLEL PATIENT TREATMENT TIME PREDICTION ALGORITHM

Abstract

Patients queue management in hospitals are tough task to handle it manually. Patient wait delays and patient
overcrowding is challenging task in hospitals. For each patient in the queue, total treatment time of all the patients
before him is the time that he has to wait. Therefore, we have got an inclination to propose a Patient Treatment Time
Prediction (PTTP) recursive to predict the waiting time for each treatment task for a patient. Through the mobile
application queue will recommend to patients. Queue will get update in real time. We have got an inclination to use
realistic patient information from various hospitals to induce a patient treatment time model for every task. Supported
this large-scale, realistic data-set, the treatment time for each patient at intervals this Queuing Recommendation (HQR)
system. As a results of the large-scale, realistic data-set and additionally the demand for fundamental quantity response,
the PTTP recursive and HQR system mandate efficiency and low-latency response. Our planned model to suggest a good
treatment arrange for patients to attenuate their wait times in hospitals.