FACE API JS OPTIMIZATION FOR ASA MEDIKA CLINIC

Abstract

Artificial Intelligence (AI) plays a pivotal role in advancing numerous sectors, with significant implications for healthcare. In the healthcare sector, manual registration processes are prone to errors and time-consuming inefficiencies. This research project aims to streamline and enhance operational efficiency at Asa Medika clinic by leveraging AI technology, specifically through the implementation of Face API JS. Face API JS, coupled with the SSD Mobilenet V1 algorithm, represents a sophisticated approach to optimizing clinic operations. By harnessing the capabilities of AI-driven facial recognition, Asa Medika aims to improve patient management processes, enhance security protocols, and expedite access to medical services. This integration not only promises to reduce administrative burdens associated with traditional registration methods but also sets a precedent for leveraging cutting-edge technology to elevate patient care standards. Through the adoption of Face API JS and the SSD Mobilenet V1 algorithm, Asa Medika clinic endeavors to establish itself as a leader in innovative healthcare solutions, paving the way for future advancements in the field of medical practice management and patient service delivery.