Human Resource Management Through Artificial Intelligence Model in the Healthcare

Abstract

The increasing complexity of the healthcare industry necessitates the recognition of human resources as a primary sustainable source of competitive advantage within healthcare management systems. This significance is magnified when healthcare professionals, physicians and nurses are considered. When human resource management (HRM) is discussed, it must be acknowledged that personnel are not devoid of emotions. The fostering of a healthy and sustainable working atmosphere is considered a critical responsibility by professional managers. In this research, a novel human resource management model is presented, which is based on AI: machine learning within the healthcare context. A deep learning model architecture based on CNN has been designed and optimized, which is trained in two scenarios through four datasets and also customized for the target hospital. The 92% accuracy is the power of the model in the recognition. The effectiveness of the model is assessed by curating a new dataset consisting of facial images of hospital professional staff displaying eight emotions: happiness, contempt, anger, sadness, disgust, fear, surprise, and neutrality. According to the post-implementation survey findings, the model has a positive impact on human resource management and enhances staff performance, making it suitable for modern and critical organizations such as hospitals and health canters. In the healthcare domain, effective communication is deemed essential for interactions with patients, as emotions play a significant role. Emotion recognition in human resource management has a profound impact not only on optimal work output but also on the relationships among personnel, clients, and the entire managed team.