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This project aims to predict the presence of heart disease based on various medical attributes of an individual. It utilizes a logistic regression model trained on a dataset containing information about patients and whether they have heart disease or not.
A RESTful API using Flask and XGBoost to predict diabetes in Pima Indians based on various diagnostic measurements. Includes training, saving the best model, and testing the API using Python requests.
This Python script fetches and saves data for ICD-10 codes from the World Health Organization (WHO) API. It traverses the entire ICD-10 hierarchy, saving each code's data as a separate JSON file.