Predictive Analytics in Healthcare
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 14628
Special Issue Editor
Interests: quality of life; PROMs; rare diseases; clinical quality registries; clinical trials; new drugs and treatments
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Predictive analytics aims to alert clinicians and caregivers of the likelihood of events and outcomes before they occur, helping them to prevent and cure health issues. It utilises various techniques including modelling, data mining, and statistics, as well as artificial intelligence to evaluate historical and real-time data and make predictions about the future. These predictions offer a unique opportunity to see into the future and identify future trends in patient care both at an individual level and at a cohort scale.
We are interested in articles that explore predictive analysis. Potential topics include, but are not limited to, the following:
- Data mining techniques and machine learning in healthcare;
- Benefits and significance of predictive analytics;
- Challenges and opportunities of big data analytics;
- Impact on care;
- Legal and ethical considerations of predictive analytics in healthcare.
Dr. Rasa Ruseckaite
Guest Editor
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Keywords
- data mining
- big data
- prediction
- machine learning
- optimization
- healthcare
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