Established in 1993, the Hellenic Complex Systems Laboratory (HCSL) is an innovative research institution dedicated to the study and optimization of non-linear multiparameter processes. Through a transdisciplinary approach, HCSL develops clinical, laboratory, research, and educational tools to enhance our understanding of complex systems. For more information on our work, please refer to HCSL publications and HCSL software.
Our research primarily focuses on the design, evaluation, and optimization of statistical quality control (QC) in clinical laboratories, measurement uncertainty evaluation and expression, diagnostic accuracy evaluation, and risk management in laboratory medicine. We also explore applications in network science, genetic search processes of genetic algorithms (GAs) and the statistics of complexity.
Notable achievements include:
1. In 1993, HCSL pioneered the genetic algorithms-based design of statistical quality control (see An introduction to design and optimization of statistical QC).
2. In 2009, we developed a theoretical framework and algorithm for optimizing statistical QC of an analytical process, based on the reliability of the analytical system and the risk of analytical error (see A note on the reliability and risk based optimization of statistical QC).
3. In 2021, HCSL introduced a novel method for calculating the uncertainty of diagnostic accuracy measures, utilizing uncertainty of measurement propagation (see HCSL Publications on diagnostic accuracy).
4. In 2022, we designed one-dimensional convolutional neural networks (NNs) to be applied to QC samples of very small size (see HCSL publications on NNs based QC).
HCSL has been a founding node of the Network of Excellence in Evolutionary Computing (Evonet), and a member organization of the Consortium for the Barcode of Life (CBOL). We have actively participated in the standards-developing committees of the Clinical and Laboratory Standards Institute (CLSI).