疾病早期预测研究综述

Mohd Nadeem Khan, Ankita Srivastava
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引用次数: 0

摘要

由于人们所选择的生活方式和所处的环境,今天的人们患有各种各样的疾病。由于在疾病的早期阶段识别和预测这些疾病变得非常重要,因此在早期阶段预测疾病的目标变得越来越重要。大多数人懒得为一个小问题去医院或看医生。我们的方法侧重于准确性,以检测额外的症状,疾病预测在医疗保健。在本节中,我仔细地使用了各种机器学习算法,并专注于这几种算法,这些算法在特定条件下达到了最高的精度,以便建立一个强大的模型,产生最准确的预测。这项工作引入了疾病预测,疾病治疗和有效的机器学习编程的本地医疗咨询的主题。世界上有几种疾病是由人们的生活习惯或周围环境引起的。因此,本研究为基于机器学习的疾病预测提供了一个总结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review Article on the Prediction of Diseases at an Early Stage
Individuals today suffer from a wide range of diseases as a result of their lifestyle choices and the environment in which they live. The objective of forecasting disease at an earlier stage becomes an increasingly vital condition as the identification and prediction of such diseases at their earlier phases become highly significant. Most individuals are too lazy to go to the hospital or see a doctor for a small problem. Our approach focuses on accuracy to detect additional symptoms for illness prediction in healthcare. In this section, I've employed a variety of machine learning algorithms carefully and focused in this few, which achieved the highest accuracy with that specific condition in order to build a strong model that produces the most exact forecasts. This work introduces the topics of illness prediction, disease therapy, and local medical consultation with effective machine learning programming. There are several diseases in the world that are brought on by the conditions of people's living habits or their surroundings. Thus, this study offers a summary of machine learning-based illness prediction.
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