A Hybrid Machine Learning and Deep Learning Approach for Diabetes Prediction With a Tkinter–Based User Interface

Diabetes prediction is a critical task in healthcare that can significantly benefit from advancements in machine learning and deep learning technologies. This paper presents a hybrid approach combining deep learning and traditional machine learning models for diabetes prediction. The proposed system integrates a Tkinter-based Graphical User Interface (GUI) to make it easier for users to interact and make predictions. In our discussion, we will cover the design and implementation of the system, and evaluate the performance of different models using precision, F1 score, recall, and, accuracy to provide insights into their effectiveness. Results demonstrate the efficacy of the hybrid approach, with a focus on model accuracy and user experience.