Artificial Intelligence in Covid-19
Description
This book deals with the advantages of using artificial intelligence (AI) in the fight against the COVID-19 and against future pandemics that could threat humanity and our environment. This book is a practical, scientific and clinically relevant example of how medicine and mathematics will fuse in the 2020s, out of external pandemic pressure and out of scientific evolutionary necessity.
This book contains a unique blend of the world's leading researchers, both in medicine, mathematics, computer science, clinical and preclinical medicine, and presents the research front of the usage of AI against pandemics.
Equipped with this book the reader will learn about the latest AI advances against COVID-19, and how mathematics and algorithms can aid in preventing its spreading course, treatments, diagnostics, vaccines, clinical management and future evolution.
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Persons
Dr. Niklas Lidströmer - Karolinska Institutet, MD, MSc, specialist physician, postgraduate researcher in AI in medicine, senior advisor in AI and medical investments, former AI entrepreneur and founder of an AI powered medical platform, former head of Medical AI at a variety of med-tech companies, and also previous co-leader of a handful of successful medical startups.
His experience also encompasses widespread global clinical work spanning 20 years within numerous regions across eight countries. After graduating with a master's thesis on global medicine in 2000, he began practicing as a medical doctor in 2002, followed by internship, specialized residencies, and clinical work all over the world, including 1 year circumnavigating as a maritime doctor.
His international work experience, fluency in nearly ten languages, practical familiarization with AI in the medical and pharmaceutical industries, and clinical specialist competence in general medicine have produced a passion for translational and educational aspects of artificial intelligence in medicine.
Dr. Niklas Lidströmer edited the pivotal reference work - the new standard reference, Artificial Intelligence in Medicine , Springer Nature (130 chapters, 1858 pages), which has now become the largest and most comprehensive in the scientific community.
Yonina Eldar is a Professor in the Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel where she heads the center for Biomedical Engineering and Signal Processing and holds the Dorothy and Patrick Gorman Professorial Chair. She is also a Visiting Professor at MIT, a Visiting Scientist at the Broad Institute, and an Adjunct Professor at Duke University and was a Visiting Professor at Stanford. She is a member of the Israel Academy of Sciences and Humanities, an IEEE Fellow and a EURASIP Fellow.
She received the B.Sc. degree in physics and the B.Sc. degree in electrical engineering from Tel-Aviv University, and the Ph.D. degree in electrical engineering and computer science from MIT, in 2002. She has received many awards for excellence in research and teaching, including the IEEE Signal Processing Society Technical Achievement Award (2013), the IEEE/AESS Fred Nathanson Memorial Radar Award (2014) and the IEEE Kiyo Tomiyasu Award (2016).
She was a Horev Fellow of the Leaders in Science and Technology program at the Technion and an Alon Fellow. She received the Michael Bruno Memorial Award from the Rothschild Foundation, the Weizmann Prize for Exact Sciences, the Wolf Foundation Krill Prize for Excellence in Scientific Research, the Henry Taub Prize for Excellence in Research (twice), the Hershel Rich Innovation Award (three times), and the Award for Women with Distinguished Contributions.
Professor Yonina Eldar received several best paper awards and best demo awards together with her research students and colleagues, was selected as one of the 50 most influential women in Israel, and was a member of the Israel Committee for Higher Education. She is the Editor in Chief of Foundations and Trends in Signal Processing, a member of several IEEE Technical Committees and Award Committees, and heads the Committee for Promoting Gender Fairness in Higher Education Institutions in Israel.
Content
1 AI and Pooling Tests for COVID-19.- 2 AI for Drug Repurposing in the Pandemic Response.- 3 AI and Point Of Care Image Analysis For COVID-19.- 4 Machine Learning and Laboratory Values in the Diagnosis, Prognosis and Vaccination Strategy of COVID-19.- 5 AI and the Infectious Medicine of COVID-19.- 6 AI and ICU Monitoring in COVID-19.- 7 Symptom Based Detection Models of COVID-19 Infection Using AI.- 8 AI Techniques for Forecasting Epidemic Dynamics: Theory and Practice.- 9 Regulatory Aspects on AI and Pharmacovigilance for COVID-19.- 10 AI and the Clinical Immunology / Immunoinformatics for COVID-19.- 11 AI, Epidemiology and Public Health in the Covid Pandemic.- 12 AI and Dynamic Sepsis Prediction in Covid-19.