Smart healt disease prediction system
| dc.contributor.author | Shaikh, Abdus Salam | |
| dc.contributor.author | Shaikh, Faiyyaz Tanvir (17CO45) | |
| dc.contributor.author | Shaikh, Soaib Riyaz (17CO48) | |
| dc.contributor.author | Shaikh, Ubed Ikram (17CO49) | |
| dc.contributor.author | Nivekar, Bilal Hamza (16DCO66) | |
| dc.date.accessioned | 2021-12-13T05:21:07Z | |
| dc.date.available | 2021-12-13T05:21:07Z | |
| dc.date.issued | 2021-05 | |
| dc.description.abstract | We are living in an era where technology is advancing at unprecedented rate. Nowadays, Artificial Intelligence and Machine Learning are used in every domain wherein machines or computers are being trained to work automatically with very less human efforts. Machine Learning Algorithms are very useful in prediction, analysis and training. We will use ML Algorithms in predicting and analysis of various diseases in human beings. Health is one of the precious asset for a human being but due to the ongoing pandemic people can’t recognize and treat their diseases from their home so we are aiming to develop a disease prediction system using ML Algorithms for better prediction of diseases by providing their symptoms to recognize the diseases more precisely with its consequences and treatment with the ease of using it at their own comfort zone. We are developing this system also because people can consult with their respective doctors via live consultation without physical contact. Our interface would help people to some extent in-order to reduce the risk associated with predicted diseases to reduce the impact on other body parts. With the help of extensive powerful ML Algorithms accuracy is highest. People can also maintain safety protocols in this pandemic by predicting the diseases from their home. Keywords: Scikit-learn, NumPy, Data Preprocessing, Dataset, Algorithms, Training Data, Training Set, Machine Learning, Naive Bayes, KNN, Decision Tree, Kernel SVM, Logistic Regression, Random Forest, Django, Training Model,Web Module, Data Collection Module, APIs, Artificial Intelligence, Disease Detection Module, Authentication, User Interface, SHDPS. | en_US |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3780 | |
| dc.language.iso | en | en_US |
| dc.publisher | AIKTC | en_US |
| dc.subject | Project Report - CO | en_US |
| dc.title | Smart healt disease prediction system | en_US |
| dc.type | Project Report | en_US |