Page 21 - Artificial Intelligence for Computational Modeling of the Heart

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what specific features in 12-lead electrocardiogram represent car-
diac function, and why they are related to heart failure. Physi-
ological modeling can complement AI-based analysis by on the
one hand enabling the exploration of new hypotheses about un-
known mechanisms; on the other hand, informing AI of physical
principles of known mechanisms to potentially address the lack
of explainability (Fig. 0.1 Artificial Intelligence). Together, AI and
computational modeling can push the knowledge frontier further
for understanding disease mechanisms in a patient-specific man-
ner and accelerate the evolution of precision medicine.
This book is a perfect introduction to the interdisciplinary
science of computational modeling and AI, and how those disci-
plines could help disrupt clinical cardiology practice. Drs. Mansi,
Passerini and Comaniciu put together the top scientists in Siemens
Healthineers at the forefront of this technological revolution. They
are among the few people who can understand and speak the lan-
guage of both quantitative and clinical sciences. This book is born
out of integrated expertise in cutting edge technologies as well
as deep understanding of challenges and limitations of the cur-
rent standard of care. This book is an exciting contribution to the
field, and it is recommended to anyone interested in using new
and bold approaches to save people’s lives and shape the health
care of the future.

Associate Professor of Medicine, MD, PhD
Hiroshi Ashikaga
Cardiac Arrhythmia Service, Division of Cardiology
Johns Hopkins University School of Medicine
Baltimore, MD, United States
September, 2019
Lund, Sweden