Abstract:
Introduction Information and communication technologies
(ICTs) have changed the trend into new integrated operations
and methods in all fields of life. The health sector has also
adopted new technologies to improve the systems and provide
better services to customers. Predictive models in health care
are also influenced from new technologies to predict the different
disease outcomes. However, still, existing predictive
models have suffered from some limitations in terms of predictive
outcomes performance.
Aims and objectives In order to improve predictive model
performance, this paper proposed a predictive model by classifying
the disease predictions into different categories. To
achieve this model performance, this paper uses traumatic
brain injury (TBI) datasets. TBI is one of the serious diseases
worldwide and needs more attention due to its seriousness and
serious impacts on human life.
Conclusion The proposed predictive model improves the predictive
performance of TBI. The TBI data set is developed and
approved by neurologists to set its features. The experiment
results show that the proposed model has achieved significant
results including accuracy, sensitivity, and specificity.
