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Length of Stay in Hospital: How to Predict the Duration of Inpatient Treatment

AltexSoft

How many days will a particular person spend in a hospital? This article describes how data and machine learning help control the length of stay — for the benefit of patients and medical organizations. In the US, the duration of hospitalization changed from an average of 20.5 Source: OECD Data. Here is a ?ouple

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Occupancy Rate Prediction: Building an ML Module to Analyze One of the Main Hospitality KPIs

AltexSoft

Read on to find out what occupancy prediction is, why it’s so important for the hospitality industry, and what we learned from our experience building an occupancy rate prediction module for Key Data Dashboard — a US-based business intelligence company that provides performance data insights for small and medium-sized vacation rentals.

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Hotel Price Prediction: Hands-On Experience of ADR Forecasting

AltexSoft

Check out our video on how revenue management works in hospitality. Before the advent of machine learning, prediction activities were largely manual, time-consuming, and relied heavily on the experience of hotel managers. But there are particular challenges associated with hotel price prediction using machine learning.

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An Extensive Guide To Understanding Predictive Models And Their Real-world Applications

U-Next

An evaluation of a sequence of data points over a period of time is carried out using this model. It is possible, for example, to predict how many patients will be admitted to the hospital next week, next month or the remainder of the year based on the number of stroke patients admitted to the hospital in the last four months. .

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Learn how to use various big data tools like Kafka, Zookeeper, Spark, HBase, and Hadoop for real-time data aggregation. They rely on Data Scientists who use machine learning and deep learning algorithms on their datasets to improve such decisions, and data scientists have to count on Big Data Tools when the dataset is huge.