Development of Workforce Diseases Detection System Using Machine Learning Models
Abstract:Health Status is one of the
important parameters determining workers’ productivity and, therefore,
significantly affects the nation’s workforce. This research work develops a
workforce disease predictive system using Machine Learning Models. The models were
trained using the five different machine learning algorithms, which include
Neural Networks, Random Forest Classifier, XGBoost, Multilayer Perceptron,
K-Nearest Neighbour, and uses an insertion sort algorithm for the second tier,
which sorts the results to analyse and select the most likely disease for each
of the workers. Hence, a system is
developed which is capable of detecting such workforce diseases. Python
programming language with Scikit Learn and TensorFlow Library was used as an
instrument for implementation. The system is more accurate and unique in
predicting workforce diseases than other existing methods or techniques