Chronic Diseases Prediction Using ML
Journal:
arXiv
Published Date:
Feb 13, 2025
Abstract
The recent increase in morbidity is primarily due to chronic diseases
including Diabetes, Heart disease, Lung cancer, and brain tumours. The results
for patients can be improved, and the financial burden on the healthcare system
can be lessened, through the early detection and prevention of certain
disorders. In this study, we built a machine-learning model for predicting the
existence of numerous diseases utilising datasets from various sources,
including Kaggle, Dataworld, and the UCI repository, that are relevant to each
of the diseases we intended to predict.
Following the acquisition of the datasets, we used feature engineering to
extract pertinent features from the information, after which the model was
trained on a training set and improved using a validation set. A test set was
then used to assess the correctness of the final model. We provide an
easy-to-use interface where users may enter the parameters for the selected
ailment. Once the right model has been run, it will indicate whether the user
has a certain ailment and offer suggestions for how to treat or prevent it.
