Pure & Applied Mathematics Geometric Group Theory Algebra & Galois Theory Mathematical Modelling & Simulation Machine Learning Applications in Healthcare Data Analysis & Statistical Methods

Cubaka ZAHINDA René is a mathematician and educator from the DR Congo. He holds a master's in mathematical sciences from AIMS Ghana (2025). His research bridges pure and applied mathematics, with projects on geometric group theory, machine learning for healthcare, and mathematical modelling. He serves as a research and teaching assistant in South Kivu (Institut Supérieur Pédagogique de Kaziba), teaching courses like linear algebra, Galois theory, and data analysis. René's goal is to pursue a PhD focused on solving real-world problems through advanced mathematical tools. Reference: Machine Learning Models for Predicting Length of Hospital Stay in the Gynecology Department of South-Kivu Hospitals: This study examines how machine learning can predict how long patients will stay in gynaecology departments in South Kivu, which helps hospitals manage beds and resources more efficiently. We analysed data from hospitals using some factors that influence hospital stays, such as patient age, diagnosis, and treatment. We performed a model that takes information at the admission of a patient. We did not integrate some factor changes that can occur while the patient is already admitted to the hospital. We tested different machine learning approaches, including generalised linear models, decision trees, and neural networks. The generalised linear model performed best, achieving 97% accuracy in predicting the length of stay. This demonstrates that machine learning can effectively support hospital planning and resource management in this setting.