TY - BOOK
T1 - Machine Learning and Artificial Intelligence in Chemical and Biological Sensing
AU - Yoon, Jeong Yeol
AU - Yu, Chenxu
N1 - Publisher Copyright:
© 2024 Elsevier Inc. All rights are reserved.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - Machine Learning and Artificial Intelligence in Chemical and Biological Sensing covers the theoretical background and practical applications of various ML/AI methods toward chemical and biological sensing. No comprehensive reference text has been available previously to cover the wide breadth of this topic. The book's editors have written the first three chapters to firmly introduce the reader to fundamental ML theories that can be used for chemical/biosensing. Subsequent chapters then cover the practical applications with contributions by various experts in the field. Sections show how ML and AI-based techniques can provide solutions for: 1) identifying and quantifying target molecules when specific receptors are unavailable 2) analyzing complex mixtures of target molecules, such as gut microbiome and soil microbiome 3) analyzing high-throughput and high-dimensional data, such as drug screening, molecular interaction, and environmental toxicant analysis, 4) analyzing complex data sets where fingerprinting approach is needed This book is written primarily for upper undergraduate students, graduate students, research staff, and faculty members at teaching and research universities and colleges who are working on chemical sensing, biosensing, analytical chemistry, analytical biochemistry, biomedical imaging, medical diagnostics, environmental monitoring, and agricultural applications.
AB - Machine Learning and Artificial Intelligence in Chemical and Biological Sensing covers the theoretical background and practical applications of various ML/AI methods toward chemical and biological sensing. No comprehensive reference text has been available previously to cover the wide breadth of this topic. The book's editors have written the first three chapters to firmly introduce the reader to fundamental ML theories that can be used for chemical/biosensing. Subsequent chapters then cover the practical applications with contributions by various experts in the field. Sections show how ML and AI-based techniques can provide solutions for: 1) identifying and quantifying target molecules when specific receptors are unavailable 2) analyzing complex mixtures of target molecules, such as gut microbiome and soil microbiome 3) analyzing high-throughput and high-dimensional data, such as drug screening, molecular interaction, and environmental toxicant analysis, 4) analyzing complex data sets where fingerprinting approach is needed This book is written primarily for upper undergraduate students, graduate students, research staff, and faculty members at teaching and research universities and colleges who are working on chemical sensing, biosensing, analytical chemistry, analytical biochemistry, biomedical imaging, medical diagnostics, environmental monitoring, and agricultural applications.
UR - http://www.scopus.com/inward/record.url?scp=85202904674&partnerID=8YFLogxK
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U2 - 10.1016/C2023-0-00229-1
DO - 10.1016/C2023-0-00229-1
M3 - Book
AN - SCOPUS:85202904674
SN - 9780443220005
BT - Machine Learning and Artificial Intelligence in Chemical and Biological Sensing
PB - Elsevier
ER -