Abstract
Early identification of risks improves patient outcomes and overall health. The early identification of high-risk status helps in early medical attention and prevents complications. Understanding a patient's risk level enables better management of chronic conditions. Identifying high-risk patients is essential for the efficient allocation of healthcare resources. This approach focuses on predicting abnormalities by analysing the correlation between multiple vital signs. This review highlights body temperature, heart rate, respiratory rate, oxygen saturation, and blood pressure as important vital signs for determining a patient's risk level. A total of 180 articles were reviewed, of which 20 were selected for inclusion. This study focuses mainly on research conducted from 2016 to 2024. The identified studies focused on critical illnesses (4, 20 %), cardiovascular diseases (4, 20 %), chronic conditions (3, 15 %), abnormalities (3, 15 %), Coronavirus Disease 2019 (COVID-19) (2, 10 %), mortality (2, 10 %), falls (1, 5 %), and hypertension (1, 5 %). Most studies have focused on physiological parameters, such as oxygen saturation, blood pressure, heart rate, respiratory rate, and body temperature. The severity level of a patient can be determined and treated by monitoring these vital signs. Developments in wearable sensor technology have facilitated the continuous monitoring of vital signs and assisted healthcare professionals.
| Original language | English |
|---|---|
| Article number | 20250120 |
| Journal | Journal of Intelligent Systems |
| Volume | 35 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 01-01-2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Software
- Information Systems
- Artificial Intelligence
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