Machine Learning Prediction of Parameters of Early Warning Scores in General Wards

Launched by KEPLER UNIVERSITY HOSPITAL · Aug 26, 2024

Keywords

ClinConnect Summary

This clinical trial is exploring how machine learning can help improve patient safety on general hospital wards. Currently, when patients are admitted, their health is monitored at certain times, but this approach might miss important changes in their condition. The goal of this study is to see if using advanced technology can help predict when a patient's health might worsen, allowing medical staff to respond more quickly and prevent serious complications.

To participate in this trial, you must be between the ages of 65 and 74 and be treated in a general hospital ward between October 2024 and October 2026. There are no specific exclusions, so if you meet the age requirement and are receiving care in the right time frame, you may be eligible. If you join, you can expect to contribute to important research that aims to enhance patient monitoring and safety, potentially benefiting many patients in the future.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Treated in general ward between 2024-10-01 and 2026-10-31 at the study center.
• Exclusion Criteria:
• • None.