TAP Systems Make Big Data Predictions for Hospital Admissions
Alyson Wyers — January 10, 2017 — Lifestyle
References: trustedanalytics.org & springwise
Parisian hospitals are using big data predictions made possible by machine learning. Trusted Analytics Platform (TAP) teamed up with Assistance Publique-Hopitaux de Paris (AP-HP) to improve health resources and predict hospital admissions.
Open source analysis platform TAP creates AI-powered tools across a variety of industries, and now four French hospitals are using their systems for open sourced time series analysis. If this groundbreaking project is considered successful, the system will be implemented across all 44 AP-HP locations to make big data predictions. Accessible with a web browser, the system can be used by administrative and clinical employees to forecast admissions over a 15 day period. This allows staffing concerns to be addressed in advance, according to demand.
This is just one example of how the health care industry is integrating new technology.
Open source analysis platform TAP creates AI-powered tools across a variety of industries, and now four French hospitals are using their systems for open sourced time series analysis. If this groundbreaking project is considered successful, the system will be implemented across all 44 AP-HP locations to make big data predictions. Accessible with a web browser, the system can be used by administrative and clinical employees to forecast admissions over a 15 day period. This allows staffing concerns to be addressed in advance, according to demand.
This is just one example of how the health care industry is integrating new technology.
Trend Themes
1. Predictive Hospital Staffing Systems - Predictive hospital staffing systems using big data and machine learning technology.
2. Big Data Predictions for Hospital Admissions - Utilizing big data to make accurate predictions for hospital admissions.
3. Open Source Time Series Analysis - Open source time series analysis tools for accurate forecasting in various industries.
Industry Implications
1. Healthcare - Opportunities for implementing predictive hospital staffing systems and improving resource allocation in healthcare.
2. Technology - Integration of big data and machine learning technology in the healthcare industry for predictive analytics.
3. Data Analysis - Utilizing open source time series analysis tools for accurate forecasting and resource optimization across industries.
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