Application of machine learning algorithm for logistic management in hospital

• Main Author: Lau, Chee Yu
• Other Authors: Li King Ho Holden
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Mechanical engineering
• Online Access: http://hdl.handle.net/10356/77438
• Institution: Nanyang Technological University

Machine learning algorithm is a topic of interest for many researchers and business sectors nowadays. Machine learning algorithm plays a major role in producing an inferred function to predict output values that can control devices or machines in applications such as autonomous vehicles, home appliance for automated systems and so on. home appliances and so on. The main objective of this study is to develop an autonomous hospital bed by applying machine learning algorithm for logistic management in hospital. The study will be done in 3 stages. First stage involves data crunching in order to convert output variable to binary form with data provided by Hospital Putra Medical Centre. Second stage is to select the machine learning algorithm by comparing the accuracy of the model. The final stage is to test the reaction and decision making of autonomous bed when sensing a patient’s critical condition. Machine learning algorithm such as Decision Tree, Logistic Regression and Random Forest have been used in this study. The evaluation that was found to be the best average accuracy score among the 3 models were Decision Tree with 90%, followed by Random Forest 86% and Logistic Regression 75%.