Clinical decision support system for chronic obstructive pulmonary disease using machine learning techniques

Sudhir Anakal, P. Sandhya
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引用次数: 22

Abstract

In last two decades, Artificial Intelligence (AI) has become a major tool in every domain in general and medical applications in particular. AI is globally accepted and used for designing medical applications to support medical practitioners in diagnosing and treating patients effectively and efficiently. Chronic Obstructive Pulmonary Disease (COPD) is a kind of obstructive lung disease. Patients suffering from COPD makes breathing uneasy. COPD's incidence of sickness and death rates are rising and it is now the fourth leading cause of death globally. In this paper, we are discussing need for Clinical Decision Support System (CDSS) for COPD which helps the physicians to provide better and effective diagnosis and treatment strategies. In addition, we have designed a CDSS for COPD which is discussed in detail in this paper. The CDSS encompasses Machine Learning techniques like Classifier Ensemble methods, Support Vector Machine, Neural Networks, and Decision Trees.
基于机器学习技术的慢性阻塞性肺疾病临床决策支持系统
在过去的二十年里,人工智能(AI)已经成为各个领域的主要工具,特别是医疗应用。人工智能已被全球接受并用于设计医疗应用程序,以支持医务人员有效和高效地诊断和治疗患者。慢性阻塞性肺疾病(Chronic Obstructive Pulmonary Disease, COPD)是一种阻塞性肺疾病。慢性阻塞性肺病患者呼吸困难。慢性阻塞性肺病的发病率和死亡率正在上升,目前已成为全球第四大死亡原因。本文探讨慢性阻塞性肺病临床决策支持系统(CDSS)的必要性,以帮助医生提供更好、更有效的诊断和治疗策略。此外,我们还设计了一个COPD的CDSS,并对其进行了详细的讨论。CDSS包含机器学习技术,如分类器集成方法、支持向量机、神经网络和决策树。
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