Welcome to

Hellenic Complex Systems Laboratory

Established in 1993, Hellenic Complex Systems Laboratory (HCSL) is an innovative virtual research laboratory dedicated to evaluating and reducing uncertainty in complex systems. Through a transdisciplinary framework, HCSL develops novel clinical, laboratory, research, and educational tools to assess and address uncertainties inherent in complex processes. For more information on the laboratory’s work, please consult Notes on HCSL Research, HCSL Publications and HCSL Software.

The principal research areas of HCSL include:
 a) Designing, evaluating, and optimizing quality control (QC) procedures in laboratory medicine.
 b) Evaluating and expressing measurement uncertainty.
 c) Investigating diagnostic accuracy assessment techniques.
 d) Applying and developing methodologies for Bayesian inference in medical diagnosis.

In addition, HCSL explores genetic algorithms (GAs), neural networks (NNs), network science and statistics in complex systems.

Notable achievements include:
 a) 1993: Introduced a genetic algorithm–based design for statistical QC (see HCSL Publications on GAs based QC).
 b) 2009: 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 HCSL Publications on QC, Reliability and Risk).
 c) 2020: Created a software tool for exploring the relation between diagnostic accuracy and measurement uncertainty (see HCSL Publications on Diagnostic Accuracy).
 d) 2021: Proposed a method for estimating the uncertainty of diagnostic accuracy measures using uncertainty propagation rules (see HCSL Publications on Diagnostic Accuracy).
 e) 2022: Designed one-dimensional convolutional NNs to be applied to QC samples of very small size (see HCSL Publications on NNs based QC).
 f) 2023: Developed a computational platform for parametric and nonparametric Bayesian medical diagnosis (see HCSL Publications on Bayesian Medical Diagnosis).
 g) 2024: Produced a software tool for parametric estimation of Bayesian diagnostic measures and their uncertainty (see HCSL Publications on Bayesian Medical Diagnosis).

HCSL has actively contributed to standards-development committees of the Clinical and Laboratory Standards Institute (CLSI) and served as a founding node of the Network of Excellence in Evolutionary Computing (Evonet).