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首页> 外文期刊>International Journal of Computer Science and Technology >Sentiment Analysis on Myocardial Infarction Using Tweets Data
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Sentiment Analysis on Myocardial Infarction Using Tweets Data

机译:使用Tweets数据分析心肌梗塞的情绪

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In 2016, the survey reports that 1.7 Million people die of Myocardial Infarction (MI), due to less medication facilities, less prevention care and treatment planning is top most analysis of effective disease risk assessment, through this we have take prevention using sentiment analysis of recent advancements, the text analytics have opened up new potential of using the rich information of tweet analysis, to identify the relevant risk factors in MI. To tackle the MI risk factors tweet analysis gives more remedy and care factors by users, also this leads to decrease of MI in India. Our system plays a machine learning approach using sentiment analysis using tweet dataset. Nowadays people suffering from MI such as cardiac arrest, high blood pressure, congestive heart failure etc. Twitter is an excellent resource for the MI Patients since they connect people who have with similar conditions and experiences. It provides the knowledge sharing about MI, plays a vital role through Opinion Mining system.
机译:在2016年,调查报告称,有170万人死于心肌梗塞(MI),这是因为有效的疾病风险评估是最主要的分析,原因是减少了用药设施,减少了预防保健和治疗计划,是我们通过情感分析来预防在最近的进展中,文本分析为利用推文分析的丰富信息来识别MI中的相关风险因素开辟了新的潜力。为了解决MI的危险因素,tweet分析为用户提供了更多的补救和护理因素,这也导致了印度MI的减少。我们的系统使用推文数据集进行情感分析,从而发挥机器学习方法的作用。如今,患有心梗,高血压,充血性心力衰竭等心肌梗死的人。Twitter是心梗患者的绝妙资源,因为他们将具有相似条件和经验的人联系在一起。它提供有关MI的知识共享,并通过Opinion Mining系统发挥至关重要的作用。

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