Recent advances in computational techniques have improved the utility of machine learning algorithms (ML) in laboratory medicine. Today, data-driven approaches and ML algorithms continue to be adopted and integrated into the complex infrastructure of health information systems (HIS) to improve clinical decision-making. In this context, clinical laboratories are trying to move from testing the technology to implementing it at scale to maximize impact and develop a ML -enabled tool to support clinical decision-making. In particular, it is important for laboratory professionals to consider and use such tools to enhance the value of clinical laboratory results.

This webinar will focus on the integration of data-driven laboratory workflows and the powerful technology of ML that offers significant potential to improve patient outcomes. The presenters have published several studies on models using multiple ML methods, and they will discuss the context using the presentations below.

Merve Sibel Güngören will give a presentation on "The role of digital transformation in improving clinical laboratory management". This will be followed by Deniz Ilhan Topçu's talk on "The Pursuits of Data Analytics and Machine learning applications in laboratory operations". The last lecture will be given by Hikmet Can Çubukçu and will cover the topic "Implementation of laboratory results in machine learning-based clinical decision support systems".