eBurnout-Text-Analysis

eBurnout is an application that serves to predict Burnout in medical personnel by analysing two types of data sources.

• A questionnaire using Maslach scale.
• By capturing and analysing psychological data like sleep and heart rate among other data...

Follow it:

• Presentation: https://www.youtube.com/watch?v=qT9e77kFbgQ
• GDPR: https://www.youtube.com/watch?v=nO3q64hrxyo
• Website: https://eburnout.com/

This Master´s Degree Thesis focuses on the application of Machine and Deep Learning algorithms to analyse and extract the value of texts and the search for hidden patterns from the European University research project called "Applications based on IoT and Big Data in the hospital environment". To do this, the entire Google Cloud Platform environment is analysed for the preparation of a comprehensive study. In the first place, a development will be carried out on an application to detect the Burnout syndrome, adapting it to the new requirements to collect, analyse and visualize the data collected from the psychiatric and emergency medical personnel from Son Llàtzer and Infanta Sofía Hospitals. Finally, it is finalised by presenting the results and conclusions obtained.

Follow it:

• Website (ES): https://eburnout.jesusgarcia.pro/index.html
• Website (EN): https://eburnout.jesusgarcia.pro/en

Key words: Machine Learning, Deep Learning, text analysis, patterns search, Big Data.

Created by Jesús García García - Master´s Degree in Big Data Analytics UEM

Made for a didactic purpose (real dataset).

*You agree not to republish and copy partly or totally this project without express authorization from owner