TY  - JOUR
AU  - Barakat, Chadi
AU  - Sharafutdinov, Konstantin
AU  - Busch, Josefine
AU  - Saffaran, Sina
AU  - Bates, Declan G.
AU  - Hardman, Jonathan G.
AU  - Schuppert, Andreas
AU  - Brynjólfsson, Sigurður
AU  - Fritsch, Sebastian
AU  - Riedel, Morris
TI  - Developing an Artificial Intelligence-Based Representation of a Virtual Patient Model for Real-Time Diagnosis of Acute Respiratory Distress Syndrome
JO  - Diagnostics
VL  - 13
IS  - 12
SN  - 2075-4418
CY  - Basel
PB  - MDPI
M1  - FZJ-2023-02448
SP  - 2098
PY  - 2023
AB  - Acute Respiratory Distress Syndrome (ARDS) is a condition that endangers the lives of many Intensive Care Unit patients through gradual reduction of lung function. Due to its heterogeneity, this condition has been difficult to diagnose and treat, although it has been the subject of continuous research, leading to the development of several tools for modeling disease progression on the one hand, and guidelines for diagnosis on the other, mainly the “Berlin Definition”. This paper describes the development of a deep learning-based surrogate model of one such tool for modeling ARDS onset in a virtual patient: the Nottingham Physiology Simulator. The model-development process takes advantage of current machine learning and data-analysis techniques, as well as efficient hyperparameter-tuning methods, within a high-performance computing-enabled data science platform. The lightweight models developed through this process present comparable accuracy to the original simulator (per-parameter R2 > 0.90). The experimental process described herein serves as a proof of concept for the rapid development and dissemination of specialised diagnosis support systems based on pre-existing generalised mechanistic models, making use of supercomputing infrastructure for the development and testing processes and supported by open-source software for streamlined implementation in clinical routines.
LB  - PUB:(DE-HGF)16
C6  - 37370993
UR  - <Go to ISI:>//WOS:001014184900001
DO  - DOI:10.3390/diagnostics13122098
UR  - https://juser.fz-juelich.de/record/1008647
ER  -