医疗保健领域大数据分析的挑战和机遇

Priyanshi Goyal, Rishabha Malviya
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引用次数: 0

摘要

数据科学是一门跨学科学科,它利用大数据、机器学习算法、数据挖掘技术和科学方法从大量结构化和非结构化数据中提取见解和信息。医疗保健行业不断创建关于患者人口统计、治疗计划、体检结果、保险范围等的大型重要数据库。物联网设备收集的数据引起了数据科学家的兴趣。数据科学可以通过处理、管理、分析和集成来帮助医疗保健行业处理大量不同、结构化和非结构化的数据。要从这些数据中获得可靠的发现,正确的管理和分析至关重要。本文对过程数据分析进行了全面的研究和讨论,因为它与医疗保健应用程序有关。本文讨论了在医疗行业使用大数据分析(BDA)的优势和劣势。BDA提供的见解也可以帮助做出战略决策,可以帮助医疗系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Challenges and opportunities of big data analytics in healthcare

Challenges and opportunities of big data analytics in healthcare

Data science is an interdisciplinary discipline that employs big data, machine learning algorithms, data mining techniques, and scientific methodologies to extract insights and information from massive amounts of structured and unstructured data. The healthcare industry constantly creates large, important databases on patient demographics, treatment plans, results of medical exams, insurance coverage, and more. The data that IoT (Internet of Things) devices collect is of interest to data scientists. Data science can help with the healthcare industry's massive amounts of disparate, structured, and unstructured data by processing, managing, analyzing, and integrating it. To get reliable findings from this data, proper management and analysis are essential. This article provides a comprehensive study and discussion of process data analysis as it pertains to healthcare applications. The article discusses the advantages and disadvantages of using big data analytics (BDA) in the medical industry. The insights offered by BDA, which can also aid in making strategic decisions, can assist the healthcare system.

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