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Machine Learning and Data Mining in Diabetes Diagnosis and Treatment

机译:糖尿病诊断和治疗中的机器学习和数据挖掘

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The remarkable progress of biotechnology and medical science has created the considerable amount of biomedical data. Diabetes mellitus (DM), a common chronic disease, has also been generated a large number of medical data in the process of diagnosis and treatment. So the exploration of medical data has become a hotpot. Nowadays, researchers are using machine learning to discover potentially valuable knowledge in medical data more than ever before. The purpose of this study is to systematically collate and review the application of machine learning, data mining method and supplement tools in the diabetes research field. Through sorting out, it was found that: a) the clinical data-sets were mainly used, b) about 82% of the articles based on diverse supervised machine learning method, c) deep learning method was widely used by researchers and the good experimental result have been achieved.
机译:生物技术和医学科学的显着进展创造了相当数量的生物医学数据。糖尿病(DM),常见的慢性疾病,也在诊断和治疗过程中产生了大量的医疗数据。因此,医疗数据的探索已成为一个热点。如今,研究人员正在使用机器学习,而不是以往任何时候都在医疗数据中发现可能的宝贵知识。本研究的目的是系统地整理和审查机器学习,数据挖掘方法和补充工具在糖尿病研究领域的应用。通过分类,发现:a)主要使用临床数据集,b)基于各种监督机器学习方法的文章约82%,c)深度学习方法被研究人员广泛使用,以及良好的实验结果已经实现。

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