Machine Learning in Personalization
Giridhar, Ritika (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202304195592
https://urn.fi/URN:NBN:fi:amk-202304195592
Tiivistelmä
Personalization has become an increasingly important aspect of human-computer interaction in recent years as it enables the adaption and customization of products and services to suit the unique needs and preferences of individual users. Personalization in healthcare has been used in a variety of areas such as precision medicine, personalized medicine, and remote patient monitoring, to provide a more useful and satisfying patient experience.
Artificial intelligence and machine learning have the potential to significantly enhance personalization in healthcare by enabling the analysis of large amounts of patient data to make predictions and provide more accurate and personalized recommendations for treatment and care.
This research project aims to investigate the applications of machine learning in personalization, with a focus on how it can be used to improve diagnosis and treatment outcomes for patients with life-threatening diseases and show why personalized treatment is necessary in 2023. The research will be conducted through a combination of literature review, a user study on how Spotify employs personalization to enhance customer satisfaction, and a case study to demonstrate how AI can optimize the personalized treatment of age-related macular degeneration.
Artificial intelligence and machine learning have the potential to significantly enhance personalization in healthcare by enabling the analysis of large amounts of patient data to make predictions and provide more accurate and personalized recommendations for treatment and care.
This research project aims to investigate the applications of machine learning in personalization, with a focus on how it can be used to improve diagnosis and treatment outcomes for patients with life-threatening diseases and show why personalized treatment is necessary in 2023. The research will be conducted through a combination of literature review, a user study on how Spotify employs personalization to enhance customer satisfaction, and a case study to demonstrate how AI can optimize the personalized treatment of age-related macular degeneration.