Implementation of Convolutional Neural Network in Medical Robot Facial Recognition System

The shortage of healthcare workers in Indonesia has led to reduced service quality and efficiency in hospitals. To address this challenge, the integration of facial verification systems in medical robot technology offers a promising solution by facilitating efficient communication and improving health services. This study presents an innovative approach utilizing Convolutional Neural Network (CNN) technology to enhance the effectiveness of patient identification. Experimental results demonstrate a significant improvement in accuracy, with the facial recognition system achieving a commendable accuracy rate of 93%. These findings highlight the potential of CNN-based facial verification systems in revolutionizing healthcare delivery.