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AN INTRODUCTION AND REVIEW ON MACHINE LEARNING APPLICATIONS IN MEDICINE AND HEALTHCARE

机译:医学与医疗保健机器学习应用的介绍与综述

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Machine learning techniques can extensively apply in the solution of the medicine domain problems by applying classification models and systems that can support medical personnel in the diagnosis and predication of diagnosis diseases. Though, it's hard to extract knowledge and information from medical records and data because this data and information is in mixed, unorganized, and high dimensional. This data also contains noise in collected data and outliers exist in collected data. Main applicable method will be used applies by checking different machine learning techniques. The performance of machine learning technique is checked by verifying and validating machine learning techniques' performances through accuracy. Present research paper has been discussing about the usability and applicability of different machine learning techniques i.e. decision tree algorithm, support vector machine method, random forest method, evolutionary algorithms based models and swarm intelligence based techniques in the diagnosis and treatment of the diseases. Advance medical diagnosis criteria generates confidence in diagnosis by using imagining techniques in the diagnosis of a disease is extensively used by doctors. In view of the fact that analyzing medical images is very complex and difficult task, by using machine learning methods for analysis of imaging will support and give major help in disease diagnosis. Application of different Machine learning methods is used by applying its techniques on big data for interpretation for diagnosis because machine learning methods show their capability and shows their easiness to solve the problems of bioinformatics domain.
机译:通过应用可以支持医务人员在诊断和预测的诊断疾病中的分类模型和系统,可以广泛地应用于药物域问题的解决方案。虽然,很难从医疗记录和数据中提取知识和信息,因为这种数据和信息是混合,无组织和高维的。该数据还包含收集的数据中的噪声,并且收集的数据中存在异常值。通过检查不同的机器学习技术,将使用主要适用的方法。通过准确性验证和验证机器学习技术的性能,检查机器学习技术的性能。目前研究论文一直在讨论不同机器学习技术的可用性和适用性,即决策树算法,支持向量机方法,随机林法,基于进化算法的基于疾病的诊断和治疗中的基于群体的型号和群体智能技术。先进的医学诊断标准通过使用医生广泛使用疾病的诊断中的想象技术产生诊断的信心。鉴于分析医学图像非常复杂和困难的任务,通过使用机器学习方法来分析成像将支持并在疾病诊断中提供主要帮助。应用不同机器学习方法的应用是通过在诊断的大数据上应用其技术来使用技术,因为机器学习方法显示其能力并表现出他们的容易解决生物信息域的问题。

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