A Framework Using Big Data for Patient Detection and Identification Systems
Shipra Saraswat, Anupama Rajesh, Gurinder Singh, Kiran Trehan, Vedant Patil, Garima Shukla, Sofia Singh
Abstract
During the COVID-19 pandemic authorities reported around 1500 missing patients/ tested positive in Delhi-NCR who were difficult to trace down. In times of calamities, natural disasters and pandemics like situations hospitals and medical centres are over occupied by patients and management, doctors and families have a hard time locating their loved ones in multiple hospitals. The human face is a unique biometric system that can determine the age, gender, mood, of an individual and even identity for verification purposes. Along with the power of deep learning and artificial intelligence, applications of machine learning is patient recognition. A state-of-the-art patient recognition is a combination of multiple machine learning and deep learning algorithms for face detection, facial recognition, facial feature extraction and finally validation. Trained based on a database, the software can provide us with information pointing out the identity of missing patients.