Real-Time AI Dashboards for ICU Monitoring and Alerting (Published)
The use of AI in developing real-time dashboards to track vital signs in Intensive Care Unit (ICU) patients is a great achievement in the medical field. It combines big data and machine learning with IoT to monitor a patient’s status and provide alerts for clinicians to act before their condition worsens. By integrating data from the various sensors used in the ICU, the system presents signs that may warn clinicians of an expected clinical change, enabling the clinicians to prevent the occurrence of the event. As evidenced by the pilot testing, the system efficiently cuts response time and minimises adverse events, thus enhancing patient outcomes. The use of CNNs and LSTMs has led to a reduction of critical incidents by 25% and an enhanced response time by 30%. Nonetheless, future studies are needed to fine-tune the system so that it can be adopted in more healthcare organisations. In summary, the described AI-powered dashboard system has great potential for improving the management of ICUs and assisting clinicians in making better decisions that could improve the quality of care provided to patients in intensive care environments.
Keywords: AI analytics, AI powered dashboards, BI reporting, ICU monitoring, critical care, healthcare technology, machine learning, predictive alerts, real-time AI