A hospital wanted to improve the quality of patient care by identifying the potential risk of diabetes in patients presenting for examination. The goal is to develop a predictive model that can provide an indication of whether a patient has a high risk of developing diabetes based on their health data and medical history.
With this predictive model, hospitals can identify patients with a high risk of diabetes earlier and provide appropriate interventions or treatments to prevent more serious disease progression. This can help patients to be more proactive in managing their health and improve overall health outcomes. In addition, hospitals can also optimize resources and planning by treating patients with potential diabetes more efficiently.
The development of predictive models requires processing complex medical data, including laboratory data, patient medical history, lifestyle, and other risk factors. In addition, it is necessary to pay attention to patient data privacy and security issues in the processing and use of this data. Models should also be thoroughly tested to ensure their accuracy and reliability before being implemented in clinical practice.
Link : https://medium.com/@rizkimahardika37/diabetes-prediction-using-streamlit-3fe193de2e45