Background:
Artificial intelligence (AI) is revolutionizing laboratory medicine, offering significant advancements in healthcare delivery. AI applications in laboratories include instrument automation, error detection, result interpretation, test utilization, genomics, and image analysis. The laboratory is an important and integral part of modern medicine. It is estimated that ۷۰% of decisions regarding diagnosis and treatment are based to some extent on laboratory results, and as a result, a significant proportion of laboratory errors can lead to misdiagnosis or delayed diagnosis, and consequently endanger the patient's life. Materials and Methods: The study was conducted based on the PICO criteria and aligned with the research objective and based on the PRISMA checklist. In this systematic review, comprehensive searches from ۲۰۱۹ to ۲۰۲۴ in PubMed, SCOPUS, Web of Science, SID and Magiran databases as well as Google Scholar search engine using Boolean operators and MESH keywords including "artificial intelligence," "analysis," and "laboratory medicine." were performed. Then the found articles were screened by two researchers separately based on the inclusion criteria. A total of ۴۸۰ articles were identified through the primary search. After checking the entry and exit criteria and critically evaluating the quality of the articles, a total of ۱۲ articles were included in the study. Results: Epidemiological studies conducted by researchers indicate that there is a huge amount of data that requires more time for manual
analysis by doctors, while artificial intelligence provides more reliable
analysis of plates and can also interpret microbial growth on plates. One study shows that one of the important applications of artificial intelligence in the field of biochemistry is the ability to predict results such as serum iron levels, which can then be used to diagnose anemia and iron deficiency in a patient. Other studies have shown that AI can help find hidden and advanced patterns in, for example, routine blood test results, detect possible cancer, and differentiate between benign and malignant masses. AI algorithms can also classify different types of blood cell images with high accuracy. Conclusion: Therefore, studies have shown that artificial intelligence plays a significant role in improving the accurate diagnosis process in laboratory diagnostic findings, as an early warning system, so that it can detect abnormalities and any disease patterns by finding patterns that go beyond the rules and manage a large volume of information well in a short period of time. However, further research is necessary to address existing challenges, such as optimizing algorithms, reducing implementation costs and addressing ethical issues.
