This new application of big data analysis and machine learning to predict admission rates is based on both internal and external data. In addition to a wide variety of resources, one form of internal ...

Hospitals in Paris are trialling Big Data and machine learning systems designed to forecast admission rates – leading to more efficient deployment of resources and better patient outcomes. It ...

In the present conditions, students regularly have difficulty finding a fitting institution to pursue higher studies based on their profile. There are some advisory administrations and online apps ...

Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records. PLOS Medicine , 2018; 15 (11): e1002695 DOI: 10.1371/journal ...

For academic institutions, choosing graduate applicants for admission is an important task. A reliable system for estimating the likelihood of a candidate being accepted into a graduate school is ...

Whether machine learning models can lead to similarly strong improvements in risk prediction in other areas of medicine requires further research. More information: PLOS Medicine (2018).

Background and Purpose— The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the ...

With the help of machine learning, big data is able to predict the number of admissions a healthcare facility will have at any given time. This predicted number will allow for these facilities to ...