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Survey on recent cancer classification systems for cancer diagnosis

机译:近期用于癌症诊断的癌症分类系统的调查

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In the present epoch of technology medical field has become one of the favorite topics of researcher and cancer is among one of them. It is a topic of concern because actual treatment of this disease is not found till date. Patients having this disease can only be saved if and only if it is found in early stage (stage I and stage II). If it is detected in latter stage (stage III and stage IV) then chance of survival will be very less. Machine learning and data mining technique will help medical field to tackle with this problem. Cancer has various symptoms such as tumor, abnormal bleeding, more weight loss etc. It is not necessary that all kinds of tumors are cancerous. Tumors are basically of two types i.e. benign or malignant. To provide appropriate treatment to the patients, symptoms must be studied properly and an automatic prediction system is required which will classify the tumor into benign or malignant. In today's internet world, bulk of data is generated on social media or healthcare websites. From this huge amount of data, symptoms can be fetched by using data mining technique, which will be further useful for cancer detection or classification. This paper makes survey of such latest research study that makes use of online and offline data for cancer classification.
机译:在当前的技术时代,医学领域已经成为研究人员最喜欢的话题之一,而癌症就是其中之一。这是一个令人关注的话题,因为直到现在还没有找到对该疾病的实际治疗方法。只有在早期(I期和II期)发现这种疾病的患者才能被保存。如果在后期(第三阶段和第四阶段)检测到,那么存活的机会将非常少。机器学习和数据挖掘技术将有助于医学领域解决这一问题。癌症具有多种症状,例如肿瘤,异常出血,更多的体重减轻等。所有类型的肿瘤不一定都具有癌性。肿瘤基本上是两种类型,即良性或恶性。为了给患者提供适当的治疗,必须适当地研究症状,并需要一个自动预测系统,它将肿瘤分类为良性或恶性。在当今的互联网世界中,大量数据是在社交媒体或医疗保健网站上生成的。通过使用数据挖掘技术可以从大量数据中获取症状,这对于癌症检测或分类将进一步有用。本文对利用在线和离线数据进行癌症分类的最新研究进行了调查。

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