![]() ![]() This proposed system foresees the chance of rising heart disease. These methods offer numerous attributes associated with heart disease. Models have been implemented using naive Bayes, random forest algorithms, and the combinations of two models such as naive Bayes and random forest methods. This research is aimed at applying recent machine learning technology to identify heart disease from past medical data to uncover correlations in data that can greatly improve the accuracy of prediction rates using various machine learning models. ![]() When it comes to prediction using traditional methodologies, the difficulty arises in the intricacy of the data and relationships. Early identification of CHD can assist to reduce death rates. According to recent studies, heart disease is said to be one of the leading origins of death worldwide. With the help of this privacy, the related user will not be compromising.Īccurate prediction of cardiovascular disease is necessary and considered to be a difficult attempt to treat a patient effectively before a heart attack occurs. The thought process of this mechanism is while uploading an image of a co-owned photo, and a request is sent to the related user based on the reply the related user gives the photo is displayed to the followers of the uploader. This paper proposes a privacy-protected mechanism based on the level of assurance the interconnected client gives to the person who uploads the picture. Sharing a picture that contains multiple clients, the person who uploads the images should consider the interconnected client's privacy. Dealing with the privacy exposure provoked by sharing snapshots that contain the faces of various end-users attracted the minds of many social media users. Despite the sensitive data the photo holds, it will be an effortless way for the evil-minded user to steal the data of those who appear in the picture. The advancement of the social communication platform, sharing snapshots, videos, and much more information has become a prominent way of retaining connections with multiple users. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |