The NeuroSymbolic Disease Predictor is an AI system that predicts diseases based on user-entered symptoms. It combines neural networks and symbolic reasoning to provide accurate and explainable predictions.
A neurosymbolic AI system implemented to predict diseases based on the symptoms entered by users. This system combines the power of neural networks and symbolic reasoning to provide accurate disease predictions, helping users make informed decisions about their health.
The system utilizes a dataset of symptoms and corresponding diseases. The dataset contains symptoms reported by patients and the corresponding diseases diagnosed by medical experts. This data is used to train the neurosymbolic AI system and capture the complex relationships between symptoms and diseases. https://www.kaggle.com/datasets/itachi9604/disease-symptom-description-dataset
The NeuroSymbolic Disease Predictor leverages a hybrid approach to disease prediction. It combines deep learning techniques with symbolic reasoning to integrate both statistical patterns and expert knowledge into the prediction process. This fusion enables the system to provide more accurate and explainable predictions.
The system uses a neural network model that has been trained on the symptom-disease dataset. It incorporates a symbolic reasoning module that utilizes the connections made in the dataset. By combining these two components, the system can capture both the complexity of symptom-disease relationships and the interpretability of the predictions.
The NeuroSymbolic Disease Predictor has demonstrated promising results in predicting diseases based on user-entered symptoms. The system achieves high accuracy in identifying the correct disease based on the symptoms provided by the user. Additionally, the symbolic reasoning module provides explanations and insights into the prediction, helping users understand the rationale behind the predictions.