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This project introduces a Critically Ill Patient Care Unit system designed to improve the management of critically ill patients and facilitate their rapid recovery. The system aims to raise healthcare professionals' situational awareness by providing instantaneous access to real-time patient vital signs and pertinent information such as IV levels. By implementing real-time dashboards and alerts, clinicians are empowered to take swift actions, significantly reducing the time traditionally spent on vital sign observations. This results in enhanced efficiency for nursing staff, who can now monitor patients conveniently from their desks and generate comprehensive reports. Moreover, the system enables doctors to closely monitor patients, intervening promptly in response to alerts signaling abnormal vital signs. Ultimately, the proposed system aims to increase the standard of care for critically ill patients, making healthcare delivery more effective and responsive.
In addition, this project incorporates an AI-Driven Medical Diagnostic System, that uses machine learning algorithms to analyze patient data and provide accurate diagnostic suggestions. This system focuses on enhancing diagnostic accuracy, reducing diagnostic time, and supporting healthcare providers with evidence-based diagnostic recommendations. By integrating AI-driven diagnostics with the ICU monitoring system, the project aims to create a comprehensive solution that monitors patient conditions in real time and Focuses on the early detection and diagnosis of potential health issues.