Predictive Analytics and Predictive Modeling in Healthcare

Sourav Mukherjee
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引用次数: 11

Abstract

Predictive analytics looks forward trying to divine unknown future trials or actions based on data mining, statistics, modeling, deep learning and artificial intelligence, and machine learning. Business Intelligence, its forerunner in analytics, is a look backward. Predictive models are useful to business activities to well understand the customers, with the goal of forecasting buying patterns, potential risks, and its possible prospects. Healthcare industry organizes predictive analytics in different ways to improve operations and minimize risk. This article will explain the understanding of predictive analytics and predictive modeling, how the healthcare industry adopted predictive analytics and modeling and the importance of data mining in healthcare.
医疗保健中的预测分析和预测建模
预测分析是基于数据挖掘、统计学、建模、深度学习和人工智能以及机器学习,试图预测未知的未来试验或行动。作为分析学的先驱,商业智能是一种回顾。预测模型对业务活动非常有用,可以很好地了解客户,其目标是预测购买模式、潜在风险及其可能的前景。医疗保健行业以不同的方式组织预测分析,以改进操作并最大限度地降低风险。本文将解释对预测分析和预测建模的理解,医疗保健行业如何采用预测分析和建模,以及数据挖掘在医疗保健中的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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