O. A. Aripov (1), M. M. Khojimurod (2)
Medical laboratories (MLs), which improve diagnostic precision and aid in clinical decision-making, are essential to the delivery of healthcare worldwide. The various contributions of machine learning (ML) are examined in this systematic review, with a focus on their significance in disease surveillance, pandemic preparedness, and the integration of cutting-edge technologies like artificial intelligence (AI). Medical laboratories provide vital diagnostic services to detect diseases like infections, metabolic abnormalities, and cancers, making them equally important to clinical procedures. By examining patient samples, they track the efficacy of treatments, allowing medical professionals to improve treatments. They also improve patient care by ensuring test accuracy through stringent quality control procedures and promoting customized medicine by customizing therapies based on genetic and molecular data. The cost of medical laboratory testing is frequently cited as the test's value, but the tests' clinical advantages are just as significant. Clinical outcome is influenced by laboratory testing, which is widely recognized to play a part in clinical decision making. Therefore, the importance of laboratory testing should be weighed against how it influences positive behaviors and results. This covers both the testing phase, which involves selecting tests that may impact clinical decision-making and the reporting phase, which directs clinical decisions and actions. If clinical decision support software and systems are focused on supporting clinical decisions addressing patient outcomes that are supported by evidence or consensus, they can increase the value of medical laboratory tests. In order to improve laboratory services and make sure they are available, effective, and able to satisfy the changing needs of healthcare systems, this evaluation emphasizes the importance of stakeholders working together. Overall, the results support the deployment of cutting-edge technology and improved laboratory infrastructures to enhance health outcomes worldwide.
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