Access to quality healthcare and doctors has always been a concern in developing countries and remote areas. To deal with such issues, this healthcare web application is developed. Healthcare data was fed to machine learning training models and engines for predictive modelling. The accuracy of these models is directly proportional to the training they get. These models will be able to predict the potential health risks to a patient a lot earlier so that they could take the preventive measures and live a long healthy life.
This healthcare web application can be accessed by the given link- https://healthcare-web-application.herokuapp.com/
A disease is an unnatural medical condition that negatively affects the functional state of an organism and is generally associated with certain signs of illness. As reported by World Health Organization (WHO), Heart Disease and Stroke are the world’s biggest killers and have remained the leading causes of death globally in the last 15 years. In the direction of predicting heart disease, Machine Learning can present remarkable features that simplify the identification of unseen patterns, eventually providing clinical insights that assist physicians in planning and providing care.
The Heart Disease dataset has been taken from Kaggle. This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. It has a total number of 303 rows and 14 columns among which 165 have a heart disease.
Data Source: Heart Disease Dataset
Liver disease is any disturbance of liver function that causes illness. The liver is responsible for many critical functions within the body and should it become diseased or injured, the loss of those functions can cause significant damage to the body. Patients with Liver disease have been continuously increasing because of excessive consumption of alcohol, inhale of harmful gases, intake of contaminated food, pickles and drugs.
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.
Data Source: Liver Disease Dataset
Breast cancer can occur in women and rarely in men. Symptoms of breast cancer include a lump in the breast, bloody discharge from the nipple and changes in the shape or texture of the nipple or breast. Its treatment depends on the stage of cancer. It may consist of chemotherapy, radiation, hormone therapy and surgery.
The dataset has been taken from UCI machine learning repository. The main objective of the analysis is to perform classification of tumors i.e., benign(B) or malignant(M). A benign tumor is a tumor that does not invade its surrounding tissue or spread around the body. A malignant tumor is a tumor that may invade its surrounding tissue or spread around the body. This dataset consists of 569 rows and 33 columns.
Data Source: Breast Cancer Dataset
Malaria is a life-threatening disease caused by parasites that are transmitted to people through the bites of infected female Anopheles mosquitoes. It is preventable and curable. The severity of malaria varies based on the species of plasmodium. Symptoms are chills, fever and sweating, usually occurring a few weeks after being bitten.
The dataset contains a total of 27,558 cell images with equal instances of parasitized and uninfected cells.
Data Source: Malaria Dataset
Pneumonia is an inflammatory condition of the lung affecting primarily the small air sacs known as alveoli. Symptoms typically include some combination of productive or dry cough, chest pain, fever and difficulty breathing. The severity of the condition is variable.
Chest X-ray images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou. All chest X-ray imaging was performed as part of patients’ routine clinical care.For the analysis of chest x-ray images, all chest radiographs were initially screened for quality control by removing all low quality or unreadable scans. The diagnoses for the images were then graded by two expert physicians before being cleared for training the AI system. In order to account for any grading errors, the evaluation set was also checked by a third expert. There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).
Data Source: Pneumonia Dataset