使用机器学习算法为健康和健康设计个性化的锻炼计划

Pub Date : 2023-09-10 DOI:10.12694/scpe.v24i3.2340
Yan Lu
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引用次数: 0

摘要

该研究论文展示了对机器学习的详细研究,该研究用于医疗保健或医疗平台,可由医疗保健专业人员使用,以采用更好的诊断仪器和工具来检查医疗问题或图像。该论文强调,机器学习算法可以用于x射线或核磁共振扫描,以检查疾病和健康问题。本文还将讨论该算法如何帮助医疗保健专业人员、医生和护士做出准确的诊断,以提供更好的服务和患者的治疗结果。在接下来的研究中使用二次研究法的一个主要优势是文献的丰富性。这里使用的所有数据都是事先收集和评估的结果,使用这些数据将增加研究的整体影响。这种方法节省了金钱、时间和人力等资源。这种研究方法允许研究者在现有的专业知识和知识的基础上建立新的知识并得出新的结论。所选择的研究哲学是解释主义研究哲学。这里选择的研究方法是归纳研究法。本研究选择的研究设计是探索性的。这些都有助于本研究实现其目的,达到本研究提出的目标。
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Using Machine Learning Algorithms to Design Personalized Exercise Programs for Health and Wellness
The research paper showcases an elaborate study of machine learning, which is used in healthcare or medical platforms and can be used by healthcare professionals to adopt better diagnostic instruments and tools for examining medical issues or images. The paper highlights that a machine learning algorithm can be utilized in X-rays or MRI scans to examine disease and health issues. This paper will also discuss how this algorithm can help healthcare professionals, doctors, and nurses make accurate diagnoses for better services and patient outcomes. One of the major advantages of using the secondary research method in the following research is the abundance of the literature. All the data being used here are previously collected and evaluated with the result, and using these will increase the impact of the study overall. This method saves resources, including money, time, and manpower. This research method allows the researcher to build new knowledge and draw new conclusions based on existing expertise and knowledge. The chosen research philosophy is the Interpretivism research philosophy. The chosen research approach here is the inductive research approach. The chosen research design for this study is exploratory. All these help the research to achieve its objectives and reach the proposed goal of this research.
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