Human Disease Prediction using Machine Learning (CNN & RandomForest)

Human Disease Prediction using Machine Learning (CNN & RandomForest)

Raghul T¹ , Prasanth P ² , Gowri V³

^1-2UG Scholar, Department of CSE, Kingston College, Vellore-59

³Asst.Professor, Department of CSE, Kingston College, Vellore-59

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      ABSTRACT

Disease Prediction system is based on predictive modeling predicts the disease of the user on the basis of the symptoms that user provides as an input to the system. The system analyzes the symptoms provided by the user as input and gives the probability of the disease as an output Disease Prediction is done by implementing the Decision tree Classifier. Decision tree Classifier calculates the probability of the disease. With big data growth in biomedical and health care communities, accurate analysis of medical data benefits early disease detection, patient care.

The objective of this study is to investigate the use of pattern classification methods for distinguishing different types of brain tumors, such as primary gliomas from metastases, and also for grading of gliomas. A computer-assisted classification method combining conventional MRI and perfusion MRI is  developed and used for differential diagnosis

Accurately predicting the survival rate of breast cancer patients is a major issue for cancer researchers. Machine learning (ML) has attracted much attention with the hope that it could provide accurate results, but its modeling methods and prediction performance remain controversial.

Adult-onset dementia disorders represent a challenge for modern medicine. Alzheimer’s disease (AD) represents the most diffused form of adult-onset dementias. Machine learning research applied to Magnetic Resonance Imaging (MRI) techniques can contribute to a faster diagnosis of AD and may contribute to predicting the evolution of the disease

Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. According to International. Diabetes is a disease caused due to the increase level of blood glucose. This high blood glucose produces the symptoms of frequent urination, increased thirst, and increased hunger.

Pneumonia is a respiratory infection caused by bacteria or viruses; it affects many individuals, especially in developing and underdeveloped nations, where high levels of pollution, Early diagnosis of pneumonia is crucial to ensure curative treatment and increase survival rates. Chest X-ray imaging is the most frequently used method for diagnosing pneumonia.

Cardiovascular disease prediction aids practitioners in making more accurate health decisions for their patients. Early detection can aid people in making lifestyle changes and, if necessary, ensuring effective medical care. Machine learning (ML) is a plausible option for reducing and understanding heart symptoms of disease.

Key Words: Machine Learning, Symptoms based disease prediction, Python.