<br />Introduction<br />The healthcare sector is witnessing a radical transformation thanks to advances in artificial intelligence (AI) technologies and the adoption of electronic health records (EHRs). Integrating AI into the analysis of these records provides a unique opportunity for a deeper understanding of patient needs and enables personalized care focused on prevention, early diagnosis, and more accurate treatment. This digital revolution represents a qualitative leap toward more efficient and sustainable healthcare systems.<br />Technical Dimension<br />Electronic health records contain vast amounts of data: medical history, test results, imaging, prescriptions, and treatment response patterns. AI, through deep learning algorithms, can rapidly analyze this data to extract precise patterns that help physicians make better-informed decisions. For example, AI can predict the likelihood of chronic diseases such as diabetes or cardiovascular conditions before symptoms appear, enabling early intervention.<br />Health Dimension<br />Traditional healthcare often relies on “averages” in diagnosis and treatment, whereas analyzing medical records with AI enables personalized care tailored to each patient’s individual needs. This reduces medical errors, improves treatment quality, and enhances the patient experience through continuous and precise monitoring.<br />Economic Dimension<br />Employing AI in data analysis reduces costs associated with delayed diagnoses or ineffective treatments. It also contributes to better management of medical resources within hospitals by reducing unnecessary hospital stays and directing medications to those most in need. These practices support the concept of economic efficiency and strengthen the sustainability of the healthcare system.<br />Social and Ethical Dimension<br />The adoption of these technologies raises important questions regarding data privacy and protection. Therefore, regulatory and ethical frameworks must be developed to ensure that AI use preserves patient confidentiality and protects their rights. From a social perspective, improving personalized healthcare helps reduce gaps among different population groups and promotes health equity.<br />Role of Innovation and Integration<br />Integrating AI with other technologies, such as the Internet of Things (IoT) and cloud computing, enhances the value of electronic health records. This integration allows continuous monitoring of patients’ health status and real-time data analysis, which increases the accuracy of care delivery.<br />Link to the Sustainable Development Goals (SDGs)<br />• Goal 3: Good Health and Well-being → By improving quality of care, enabling early diagnosis, and reducing medical errors.<br />• Goal 9: Industry, Innovation, and Infrastructure → Through adopting AI as an innovative tool that strengthens the digital infrastructure of the healthcare sector.<br />• Goal 10: Reduced Inequalities → By providing personalized healthcare to all individuals, including disadvantaged groups, ensuring fairness in access to medical services.<br />• Goal 12: Responsible Consumption and Production → By improving resource management and reducing waste in treatments and medications.<br />Conclusion<br />Analyzing electronic health records using AI is not just a technical tool but a strategic step toward more accurate, inclusive, and sustainable healthcare. It paves the way for intelligent and equitable health systems capable of addressing current challenges while ensuring a healthier future for generations to come.<br /><br />Al-Mustaqbal University – The First University in Iraq.<br /><br />