This project aims to provide a statistical analysis of medical records from patients who suffered a heart failure. The first part of the study uses statistical techniques to identify the features of significance in the mortality prediction, and a survival analysis completes the findings. The finality of this project is to build a model that predicts the outcome of a heart failure as well as the expected survival time of a patient.
Hospitals have been moving towards the adoption of digitalised systems, and the management of patients’ data through Electronic Health Records (EHR) is a major opportunity to explore high-quality medical datasets. This research is also an attempt to demonstrate how Data Analytics can shed some light on any type of information, regardless of the domain complexity, as long as the techniques are thoroughly applied and the interpretations cautiously approached.
The opportunities presented by the increased availability of anonymized Electronic Health Records will only grow overtime and exploring them could lead to discoveries that would eventually contribute to saving lives.
Final year computing student specialising in Data Analytics. I moved to Ireland for an Erasmus+ internship in 2015 and I was offered a permanent position in another company in 2016.
After two years working full-time and countless self-learning hours, I decided to formally advance my education by pursuing a part-time degree. My career goal is to become an experienced data analyst with an expertise in MS Excel and MS Power BI.
I also have a keen interest in learning the other components of the MS Power Platform. I am currently working as a data analyst in the semiconductor industry.