Prepared by: Prof. Dr. Younis Abdul Redha Al-Khafaji<br />Introduction:<br />The past decade has witnessed a radical transformation in the healthcare sector, with artificial intelligence (AI) becoming an indispensable ally for doctors and researchers. Among its many applications, AI has emerged as a highly accurate and rapid tool for diagnosing viral infections, opening new horizons for saving lives and combating epidemics.<br />How does AI aid in diagnosis?<br />AI analyzes massive amounts of medical data at a speed far beyond human capability. Its contributions can be seen in several areas:<br /> 1. Medical image analysis: AI is trained on millions of radiological images, such as X-rays and CT scans of the lungs. It can detect signs of viral infections (e.g., COVID-19 and influenza) with remarkable accuracy, sometimes even before clear symptoms appear in the patient.<br /> 2. Early diagnosis through data: AI examines patient data, including initial symptoms, routine blood test results, and medical histories. By recognizing hidden patterns, it can predict the likelihood of infection by a specific virus and guide physicians to conduct confirmatory tests early.<br /> 3. Accelerating molecular test analysis: AI assists in analyzing PCR and genetic sequencing results, reducing result turnaround time from hours to minutes in some experimental models, while increasing the accuracy of interpretation.<br />Recent scientific developments:<br /> • Discovery of new viruses: Researchers have developed intelligent algorithms capable of analyzing genetic material in patient samples to detect previously unknown viruses or mutations in existing viruses, enabling early epidemic alerts.<br /> • Automated differential diagnosis: Advanced AI systems can now distinguish between viral and bacterial infections based on data analysis, reducing unnecessary use of antibiotics.<br /> • AI in virtual laboratories: Recent trends involve integrating AI with technologies such as digital pathology, where microscope slides are converted into high-resolution digital images for automated analysis of viral markers.<br />Challenges and the future of the sector:<br />Despite these achievements, challenges remain, including the need for massive and secure datasets to train models, ensuring transparency of algorithms (“black box” issues), and seamless integration of these technologies into current healthcare systems.<br />Undoubtedly, AI developers are working steadily to make AI a cornerstone of the future of medical diagnostics. AI cannot replace the physician, but it enhances their capabilities, providing exceptional tools to make faster and more accurate decisions, ultimately improving healthcare quality and saving human lives.<br /><br />Al-Mustaqbal University the First in Iraq