Established in 1993, Hellenic Complex Systems Laboratory (HCSL) is an innovative research laboratory committed to the evaluation and reduction of uncertainty in complex systems. Through a transdisciplinary approach, HCSL develops clinical, laboratory, research, and educational tools to assess and address the uncertainty associated with complex processes. For more information on our work, please refer to HCSL publications and HCSL software.
Our primary research areas are:
a) The design, evaluation, and optimization of quality control (QC) in laboratory medicine.
b) Measurement uncertainty evaluation and expression.
c) Diagnostic accuracy assessment.
d) The application of Bayesian inference for medical diagnosis.
We have also explored applications in network science, genetic search processes of genetic algorithms (GAs) and the statistics of complexity.
Notable achievements include:
a) In 1993, HCSL pioneered the GAs based design of statistical QC (see An introduction to design and optimization of statistical QC).
b) 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).
c) 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).
d) 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).
e) In 2023, HCSL developed a a Bayesian inference based computational tool for parametric and nonparametric medical diagnosis (see HCSL publications on Bayesian inference for medical diagnosis).
We have actively participated in standards-developing committees of Clinical and Laboratory Standards Institute (CLSI). In addition, 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).