Healthcare Project App ❤

All Health Care Models At One Place 🥀

If you want to view the deployed model, click on the following link:

• xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Preview

Problem Statement

Liver Disease : This data set contains 416 liver patient records and 167 non liver patient records collected from North East of Andhra Pradesh, India. The "Dataset" column is a class label used to divide groups into liver patient (liver disease) or not (no disease). This data set contains 441 male patient records and 142 female patient records. Use these patient records to determine which patients have liver disease and which ones do not.
Heart Disease : This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4. The names and social security numbers of the patients were recently removed from the database, replaced with dummy values. One file has been "processed", that one containing the Cleveland database. All four unprocessed files also exist in this directory. Use these records to determine which patients have heart disease or not.
Diabetes Disease : This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage. The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and so on.
Stroke Prediction : According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths. This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relavant information about the patient. Create machine learning model for predicting whether the patients has stroke or not.
Breast Cancer Disease : This dataset contain 569 wisconsin diagnostic breast cancer patients reocrds out of which 357 are benign and 212 are malignant. Use these records to determine which patients have breast cancer disease and which ones do not.
Chronic Kidney Disease : The data was taken over a 2-month period in India with 25 features ( eg, red blood cell count, white blood cell count, etc). The target is the 'classification', which is either 'ckd' or 'notckd' - ckd=chronic kidney disease. There are 400 rows. Create machine learning model for predicting whether the patients has chronic kidney disease or not.