Wednesday, August 30, 2023
7:00 a.m.
Online presentation from KTH in Sweden
https://www.digitalfutures.kth.se/event/systems-engineering-methodology-for-healthcare-information-highways-hospital-management-disease-biology-and-modern-pharmaceuticals/
Systems Engineering Methodology for Healthcare Information Highways, Hospital Management, Disease Biology and Modern Pharmaceuticals
John Baras
Distinguished University Professor
Lockheed Martin Chair in Systems Engineering
Institute for Systems Research
Electrical and Computer Engineering Department
University of Maryland
Zoom presentation live from KTH in Sweden.
Zoom: https://kth-se.zoom.us/j/69560887455
Meeting ID: 695 6088 7455
Password: 755440
Abstract
A rigorous Model-Based Systems Engineering (MBSE) methodology and its application to several problems related to Systems Healthcare, Systems Medicine and Systems Biology.
First, we develop an Information Highway for Health Care Management Systems with Diabetes Mellitus as the driving example. We describe the desired architecture of such systems. We include a Controlled Hidden Markov Chain model for diabetes disease progression with three states, three diagnostic tests, ten interventions, three types of patients. We develop three methods for computing tradeoffs between health care cost and health care quality. We demonstrate the powerful capabilities of such a framework via examples and problems of practical healthcare significance.
Next, we develop a methodology and framework for managing Intensive Care Units (ICU) and hospitals, that integrates financial modeling, patient flow, and progression of patient condition. Model parameters were estimated from data. We describe sensitivity analysis to demonstrate themodel’s usefulness. We show specific examples for the care of patients with severe traumatic brain injury (STBI) in an ICU. The approach can be applied in many other use cases and settings.
Then, we describe a Systems Biology model for Alzheimer’s disease that integrates the interactions between neurons, astrocytes, microglia, brain endothelial cells, blood circulation in the brain. The model allows, via simulations, to study pathological changes that are observed in the brains of AD patients, including diffuse beta amyloid (Aβ) plaques, hyper-phosphorylated TAU protein that disrupts axonal transport, neuroinflammation and mitochondrial dysfunction, effects of lipid metabolism and cholesterol levels in the brain and plasma.
We also describe our initial ideas and most recent developments of “Lab-on-a-chip”, including in-vivo cells of human organs. One goal is to study the side effects of specific medicines for a disease classified according to human phenotypes (for precision medicine and pharma).
We close with current efforts to integrate data-driven (i.e. ML and AI) and model-based systems engineering methods in many use cases.
ohn S. Baras is a Distinguished University Professor holding the Lockheed Martin Chair in Systems Engineering with the Institute for Systems Research (ISR) and the ECE Department at the University of Maryland College Park. He received his Ph.D. degree in Applied Mathematics from Harvard University, in 1973, and he has been with UMD since then. From 1985 to 1991, he was the Founding Director of the ISR. Since 1992, he has been the Director of the Maryland Center for Hybrid Networks (HYNET), which he co-founded.
He is a Fellow of IEEE (Life), SIAM, AAAS, NAI, IFAC, AMS, AIAA, Member of the National Academy of Inventors (NAI) and a Foreign Member of the Royal Swedish Academy of Engineering Sciences (IVA). Major honors and awards include the 1980 George Axelby Award from the IEEE Control Systems Society, the 2006 Leonard Abraham Prize from the IEEE Communications Society, the 2017 IEEE Simon Ramo Medal, the 2017 AACC Richard E. Bellman Control Heritage Award, and the 2018 AIAA Aerospace Communications Award. In 2016 he was inducted in the University of Maryland Clark School of Engineering Innovation Hall of Fame.
In June 2018 he was awarded a Doctorate Honoris Causa by his alma mater the National Technical University of Athens, Greece. He has mentored 101 doctoral students, 135 MS students and 70 postdoctoral fellows, who have gone to excellent careers in industry, academia and government. His research interests include systems, control, optimization, autonomy, machine learning, artificial intelligence, communication networks, applied mathematics, signal processing and understanding, robotics, computing systems, formal methods and logic, network security and trust, systems biology, healthcare management, model-based systems engineering. He has been awarded nineteen patents, one software copyright, and honored with many awards world-wide, as innovator and leader of economic development.