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dc.contributor.author Project Supervisor Dr. Mahrukh Liaqat, Abdul Moiz Muhammad Mustafa Shahid Javeria Sultan Muhammad Hassaan Kashif
dc.date.accessioned 2025-02-13T08:24:44Z
dc.date.available 2025-02-13T08:24:44Z
dc.date.issued 2024
dc.identifier.other DE-ELECT-42
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/49865
dc.description Project Supervisor Dr. Mahrukh Liaqat en_US
dc.description.abstract In the domain of health monitoring, there is a dire need for accurate and innovative solutions that can optimize the efficiency and make the medical procedures cost inefficient. Our project introduces an innovative approach by incorporating Artificial Intelligence (AI) and Embedded Systems to assemble a Complete Blood Count (CBC) kit. Utilizing advanced machine learning algorithms to swiftly and effectively analyze real-time blood samples making it one of its kind. Personalized health assessment, early anomaly detection, vitals trend analysis and empowering users with an accessible health management tool are our value proposition. Integration of Raspberry Pi 5 and camera verifies its maneuverability and accessibility. Comprehensive report generation via web application, fulfilling the purpose of save, review and research. This advanced technology ensures sustainability for diverse healthcare environment, facilitating accuracy and cost efficient solutions to crucial health monitoring practices. Cloud computation covering for the resources cost to run this project, provides safe storage and computational power to tackle this tool’s need in divergent environments. This project represents a compelling contribution to the growth of personalized diagnostics and wellness management. en_US
dc.language.iso en en_US
dc.publisher College of Electrical and Mechanical Engineering (CEME), NUST en_US
dc.title AI-Based CBC en_US
dc.type Project Report en_US


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