Human Symptom Analysis for Multi-Disease and Prediction using PyCharm and Machine Learning
In recent years, machine learning frameworks for medical analysis have predominantly focused on individual diseases, with separate models developed for conditions like skin diseases, cancer, and diabetes. However, these systems are often limited in their ability to predict multiple diseases simultaneously using a single approach. This research proposes a machine learning-based method for predicting the prognosis of various diseases through a unified system. The study analyzes a range of diseases, including diabetes, heart disease, retinopathy, breast cancer, and lung diseases, using a variety of patient symptoms. The system is designed to incorporate additional conditions, such as skin disorders and fever, in future iterations.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-12-31
- DOI
- https://doi.org/10.5281/zenodo.14581110
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00