The reliability of clinical research results depends not only on data quality. Choosing the right statistical methods is just as important as data collection. An inappropriate analysis method can lead to misinterpretation and incorrect conc...

Artificial intelligence and machine learning are increasingly used in health research. They offer important opportunities especially for disease risk prediction, forecasting clinical outcomes, and supporting diagnostic decisions. Building a...

Clinical laboratory tests play an important role in diagnosing disease, monitoring treatment, and assessing patients’ health status. Correct interpretation of laboratory results depends not only on knowing the measured value. The reference...

Digital technologies are creating new application opportunities across healthcare delivery and the training of health professionals. Mobile apps, virtual reality (VR), and digital decision-support systems are among the technologies increasi...