Predictive Analytics in Healthcare : utilising big data for disease prevention and treatment
Dhaimash, Mafas (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024060420949
https://urn.fi/URN:NBN:fi:amk-2024060420949
Tiivistelmä
The objective of this thesis was to research the use of predictive analytics in healthcare, specifically focusing on the utilisation of big data for disease prevention and treatment. This thesis highlights the significant role of predictive analytics in healthcare, while studying the potential benefits and challenges related to the use of big data in medical contexts.
The research materials mainly consisted of existing literature on big data in healthcare, including its definition, data sources, benefits and challenges. Additionally, predictive modelling techniques, specifically machine learning algorithms were researched for their efficacy in healthcare. Case studies were analysed to demonstrate successful applications.
The results of this research indicate that while predictive analytics provides significant improvements to healthcare, there are various challenges and concerns to consider. Future development should focus on improving these analytics methods as well as finding solutions for the current challenges.
The research materials mainly consisted of existing literature on big data in healthcare, including its definition, data sources, benefits and challenges. Additionally, predictive modelling techniques, specifically machine learning algorithms were researched for their efficacy in healthcare. Case studies were analysed to demonstrate successful applications.
The results of this research indicate that while predictive analytics provides significant improvements to healthcare, there are various challenges and concerns to consider. Future development should focus on improving these analytics methods as well as finding solutions for the current challenges.