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dc.contributor.author | Muhammad Taimoor Ather, 01-135202-065 | |
dc.contributor.author | Saira Riasat, 01-135202-081 | |
dc.date.accessioned | 2024-08-19T06:22:08Z | |
dc.date.available | 2024-08-19T06:22:08Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | http://hdl.handle.net/123456789/17703 | |
dc.description | Supervised by Dr. Hafiz Ishfaq Ahmed | en_US |
dc.description.abstract | In contemporary healthcare settings, the pre-surgical phase often presents significant challenges due to manual review processes and fragmented data access. This conventional approach results in inefficiencies, delays, and potential risks in patient care. To address these shortcomings, this project proposes an innovative Electronic Health Record (EHR) system with predictive capabilities tailored for pre-surgical patient care. By harnessing advanced image-based data input and predictive analytics, our solution revolutionizes the traditional approach to pre-surgical assessments. The proposed EHR system offers a proactive solution by automaticallypredicting patient health status before surgery. Through comprehensive analysis of diverse medical parameters, including blood tests, radiological images, and cardiac assessments, our system empowers healthcare professionals with valuable insights for informed decision-making. By streamlining record maintenance and enhancing data accessibility, our solution promises to optimize clinical workflows, improve patient outcomes, and ultimately transform pre-surgical patient care. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Computer Sciences | en_US |
dc.relation.ispartofseries | BS(IT);P-02222 | |
dc.subject | Pre Surgery | en_US |
dc.subject | Sentinel | en_US |
dc.subject | Medi Track | en_US |
dc.title | Pre Surgery Sentinel and Medi Track | en_US |
dc.type | Project Reports | en_US |