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DC Field | Value | Language |
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dc.contributor.author | Sinha, Harshit | - |
dc.contributor.author | Singh, Tiratha Raj [Guided by] | - |
dc.contributor.author | Mohana, Rajni [Guided by] | - |
dc.date.accessioned | 2023-09-08T10:50:30Z | - |
dc.date.available | 2023-09-08T10:50:30Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9885 | - |
dc.description | Enrolment No. 191305 | en_US |
dc.description.abstract | Modern people suffer from various diseases due to their environment and lifestyle. This disease claims the lives of many people. As a result, predicting disease early becomes an important task. Many researchers have developed new techniques to predict disease early, before it's too late. This benefits both medicine and people. However, doctors find it difficult to make accurate predictions based on symptoms. The most difficult challenge is accurately predicting disease. Machine learning will play a key role in overcoming this problem by predicting disease. Medicine generates an enormous amount of data each year. Proper analysis of medical data benefits early patient care due to the increase in data in the medical and healthcare field. Machine learning algorithms use disease data to uncover pattern information hidden in vast amounts of medical data. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Chronic kidney disease | en_US |
dc.subject | K- nearest neighbor | en_US |
dc.subject | Diabetes | en_US |
dc.title | Development of Application For Bio -Medical and Health Data Using ML Approaches to Predict Health Conditions | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Development of application for bio medical and health data using ML approaches to predict health conditions.pdf | 5.3 MB | Adobe PDF | View/Open |
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