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dc.contributor.authorSONI YADAV, 20SCSE010008 –
dc.date.accessioned2022-07-29T09:49:21Z
dc.date.available2022-07-29T09:49:21Z
dc.date.issued2022-05
dc.identifier.urihttp://10.10.11.6/handle/1/9976
dc.description.abstractThe rapid increase of Internet technology and Machine learning devices has opened up new avenues for the online healthcare system. There are situations where online medical help or healthcare advice is easier or faster to grasp than real-world assistance. People often feel unwilling to go to the hospital or physicians on minor symptoms, and instead, they post their health-related queries on various healthcare forums. For this consideration, predictions may not always be accurate, and there is no assurance that users will always get a reply to their posts. Also, some posts are made up, which can drive the patient in the wrong direction.en_US
dc.language.isoenen_US
dc.publisherGalgotias Universityen_US
dc.subjectOAPen_US
dc.subjectMachine Learning enabled M-Theory.en_US
dc.subjectMACHINE LEARNING ALGORITHM FOR ONLINE AUTOMATIC PREDICTION OF DISEASEen_US
dc.subjectM.TECH IN COMPUTER SCIENCE AND ENGINEERINGen_US
dc.titleMACHINE LEARNING ALGORITHM FOR ONLINE AUTOMATIC PREDICTION OF DISEASE COMMON ATTRIBUTES USING NEVER- ENDING IMAGE LEARNERen_US
dc.typeOtheren_US


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