This book is intended for medical students and advanced undergraduates such as physicists and mathematicians with inter-disciplinary interests, biophysicists, medical physicists, applied mathematicians and others who wish to understand medicine in mathematical terms as well as current mathematical applications in physiology and medicine. The mathematical presentation is clear and self-contained.This book, representing 15 years of work at RAND Corporation and USC on chemotherapy, pharmacokinetics and nuclear medicine, attempts to direct medical scientists towards mathematical aspects of problems in medicine. The book begins with an introduction to compartmental models and matrix theory, highlighting the advantages of the approach. Discussions on how questions in observations and testing lead to multi-point boundary value problems are presented. The potentials of the digital computer in the bio-medical field are examined. A new approach — dynamic programming — to overcome clinical constraints is covered in detail. The reader should obtain a broad impression of where future research opportunities in the biochemical field lie.

This book is intended for medical students and advanced undergraduates such as physicists and mathematicians with inter-disciplinary interests, biophysicists, medical physicists, applied mathematicians and others who wish to understand medicine in mathematical terms as well as current mathematical applications in physiology and medicine. The mathematical presentation is clear and self-contained.This book, representing 15 years of work at RAND Corporation and USC on chemotherapy, pharmacokinetics and nuclear medicine, attempts to direct medical scientists towards mathematical aspects of problems in medicine. The book begins with an introduction to compartmental models and matrix theory, highlighting the advantages of the approach. Discussions on how questions in observations and testing lead to multi-point boundary value problems are presented. The potentials of the digital computer in the bio-medical field are examined. A new approach — dynamic programming — to overcome clinical constraints is covered in detail. The reader should obtain a broad impression of where future research opportunities in the biochemical field lie.

The classical theory of the Laplace Transform can open many new avenues when viewed from a modern, semi-classical point of view. In this book, the author re-examines the Laplace Transform and presents a study of many of the applications to differential equations, differential-difference equations and the renewal equation.

This book aims to present an overview of stochastic system reliability modeling for undergraduate and graduate students, engineers and researchers. It is ideal as a one-semester undergraduate or graduate level text in reliability, applied stochastic processes, stochastic operations research and systems engineering. The topics are divided into two parts: The first part deals with probability theory and stochastic processes, which provide the basic ideas of applied stochastic processes and the second part treats their applications to system reliability modelling. Throughout the later half, Markov renewal processes are applied to formulating stochastic models for system reliability. Since a fairly intermediate level of mathematics is assumed two appendices on Laplace-Stieltjes transforms and signal flow graphs provide much background material. The text is pedagogically sound.

This book is intended for medical students and advanced undergraduates such as physicists and mathematicians with inter-disciplinary interests, biophysicists, medical physicists, applied mathematicians and others who wish to understand medicine in mathematical terms as well as current mathematical applications in physiology and medicine. The mathematical presentation is clear and self-contained.This book, representing 15 years of work at RAND Corporation and USC on chemotherapy, pharmacokinetics and nuclear medicine, attempts to direct medical scientists towards mathematical aspects of problems in medicine. The book begins with an introduction to compartmental models and matrix theory, highlighting the advantages of the approach. Discussions on how questions in observations and testing lead to multi-point boundary value problems are presented. The potentials of the digital computer in the bio-medical field are examined. A new approach — dynamic programming — to overcome clinical constraints is covered in detail. The reader should obtain a broad impression of where future research opportunities in the biochemical field lie.

This book is intended for medical students and advanced undergraduates such as physicists and mathematicians with inter-disciplinary interests, biophysicists, medical physicists, applied mathematicians and others who wish to understand medicine in mathematical terms as well as current mathematical applications in physiology and medicine. The mathematical presentation is clear and self-contained.This book, representing 15 years of work at RAND Corporation and USC on chemotherapy, pharmacokinetics and nuclear medicine, attempts to direct medical scientists towards mathematical aspects of problems in medicine. The book begins with an introduction to compartmental models and matrix theory, highlighting the advantages of the approach. Discussions on how questions in observations and testing lead to multi-point boundary value problems are presented. The potentials of the digital computer in the bio-medical field are examined. A new approach — dynamic programming — to overcome clinical constraints is covered in detail. The reader should obtain a broad impression of where future research opportunities in the biochemical field lie.

The classical theory of the Laplace Transform can open many new avenues when viewed from a modern, semi-classical point of view. In this book, the author re-examines the Laplace Transform and presents a study of many of the applications to differential equations, differential-difference equations and the renewal equation.

This book aims to present an overview of stochastic system reliability modeling for undergraduate and graduate students, engineers and researchers. It is ideal as a one-semester undergraduate or graduate level text in reliability, applied stochastic processes, stochastic operations research and systems engineering. The topics are divided into two parts: The first part deals with probability theory and stochastic processes, which provide the basic ideas of applied stochastic processes and the second part treats their applications to system reliability modelling. Throughout the later half, Markov renewal processes are applied to formulating stochastic models for system reliability. Since a fairly intermediate level of mathematics is assumed two appendices on Laplace-Stieltjes transforms and signal flow graphs provide much background material. The text is pedagogically sound.