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Computers and Mathematical Models in Medicine
BOOK
REVIEW
C. Vallbana, eds., Computers and Mathematical Models in Notes in Medical Informatics, Springer-Verlag, New 1981, vii+ 315 pp., $26.50, paper
D. Cardus
and
Medicine Vol. 9, Lecture York,
The papers in this book were presented at the medical sessions of the First Conference on Mathematics at the Service of Man held in Barcelona, Spain, in July, 1977. As stated in the preface, “the principal purpose of the conference was to underscore the fact the mathematics is a science whose applications are relevant to many aspects of human activity.” Indeed, the last few years have seen an exponential growth in the applications of mathematics in the medical sciences. However, it is just this fact that makes it difficult to review this volume. Although the book was printed in 1981, most of the papers are still of 1977 (or earlier) vintage. Since this review is being written in 1984, I have the difficulty that what was current in 1977 may have only historical interest today. Many of the most promising approaches today are not menfioned because they were not around or were in their extreme infancy when the book was written. Therefore I will try and annotate this review with current material where possible. The book contains 19 articles by 38 authors broken into four chapters (Models and Computers in Signal Processing (2 articles); Mathematical and Statistical Models in Physiopathology (5); Models and Computers in Medical Diagnosis (6); and Models and Computers in Health Services Delivery (6)). Generally, the articles are well written and should be accessible to anyone with a good undergraduate background in mathematics, although some of the statistical articles may require more detailed knowledge. By far the longest article (about one-quarter of the book) is the review of medical image processing by J. Prewitt. In it she concentrates on two fields where she has made seminal contributions: the automatic classification of white blood cells by video-based image microscopic systems, and computerized tomagraphic reconstruction (CAT Scanning). As noted, about 300 million blood smears are read annually in the United States at a cost of about 1.5 billion dollars. Such volume leads to manual errors which have implications on the everyday working of the clinician. Therefore much work has been done over the last 20 years to develop an automated detection system able to perform differential counting and other blood cytological tasks. Several such commercial machines are now on the market. Dr. Prewitt discusses the major problems of image articulation, image description, feature selection for discrimination, and statistical classification. She takes a case-study approach, showing how she and her coworkers developed their scheme. The techniques described are applicable to many other problems, as MATHEMATICAL
BIOSCIENCES
75:139-140
(1985)
139
OElsevier Science Publishing Co., Inc., 1985 52 Vanderbilt Ave., New York, NY 10017
0025-5564/85/$03.30
BOOK REVIEW
140
attested to by the current explosion of literature. One minor criticism is that the bibliography is almost exclusively made up of her own work, perhaps misleading the reader to believe that it is not an active field. Also, in addition to medical diagnosis, image analysis is now leading the way to basic biological discoveries
VI. The CAT reconstruction problem is of profound medical importance that affects numerous patients. Various algorithms are reviewed and future developments are outlined. Of course, the future is now past and even as Dr. Prewitt notes in a 1980 postscript, the field is rapidly developing. Today medical imaging is expanding and many new technologies are emerging, each of which requires mathematical analysis (ultrasound, whole body NMR, etc.) [2]. The section on mathematical and statistical models in physiopathology contains one review paper on mathematical oncology and four specific application papers. Upon reading this section the reader might get the impression that most modeling in medicine must be statistical in nature (an opinion that many modelers also hold). However, although medical data must be noisy by its very nature, there is a definite role for deterministic modeling in medicine and biology. In fact, one can argue that because many systems in biology are designed to compensate for random inputs, such stochastic effects are controlled for, thus allowing successful deterministic modeling. The articles in the section on medical diagnosis mainly use statistical decision theoretical approaches to diagnose various diseases. Today such endeavors are usually approached via expert systems: a group of rules and reasoning capable of simulating the decision strategy of the clinician. Such shining stars as MYCIN and INTERNIST have shown the usefulness of the technology [3]. The last section deals with health service delivery (except for the paper on optimal scheduling of cancer radiotherapy, which should rightly be in the modeling section, and which is an excellent treatment of the subject). The need for modeling to determine optimal allocation of health care resources has been emphasized in recent years by the skyrocketing costs of medical treatment. The papers presented here take a step in this direction. Such forward-looking modeling is needed, however this reviewer is not aware of a conserted modeling effort in this field. All in all, the papers in this book will provide both the neophyte and expert with some food for thought. Because of its low price, I think is deserves to be on the library shelf. The review of image analysis, although limited, is itself worth the cost. REFERENCES [l] [2] [3]
C. Nicolini, Ed., Cell Growth Plenum Press, 1982. For a mathematical introduction into some of the newer technologies, see Albert Macovski, Medical Imaging Sysrem, Prentice-Hall, 1983. A. Barr and E. Feigenbaum, Eds. The Handbook of Artificial Intelligence, Vol. II, William Kaufmann, Inc. 1982.
STANLEY ZIETZ Departments of Mathematics and Computer Science and Biomedical Sciences and Engineering Institute Drexel University Philadelphia, Pennsylvania 19104
REVIEW
C. Vallbana, eds., Computers and Mathematical Models in Notes in Medical Informatics, Springer-Verlag, New 1981, vii+ 315 pp., $26.50, paper
D. Cardus
and
Medicine Vol. 9, Lecture York,
The papers in this book were presented at the medical sessions of the First Conference on Mathematics at the Service of Man held in Barcelona, Spain, in July, 1977. As stated in the preface, “the principal purpose of the conference was to underscore the fact the mathematics is a science whose applications are relevant to many aspects of human activity.” Indeed, the last few years have seen an exponential growth in the applications of mathematics in the medical sciences. However, it is just this fact that makes it difficult to review this volume. Although the book was printed in 1981, most of the papers are still of 1977 (or earlier) vintage. Since this review is being written in 1984, I have the difficulty that what was current in 1977 may have only historical interest today. Many of the most promising approaches today are not menfioned because they were not around or were in their extreme infancy when the book was written. Therefore I will try and annotate this review with current material where possible. The book contains 19 articles by 38 authors broken into four chapters (Models and Computers in Signal Processing (2 articles); Mathematical and Statistical Models in Physiopathology (5); Models and Computers in Medical Diagnosis (6); and Models and Computers in Health Services Delivery (6)). Generally, the articles are well written and should be accessible to anyone with a good undergraduate background in mathematics, although some of the statistical articles may require more detailed knowledge. By far the longest article (about one-quarter of the book) is the review of medical image processing by J. Prewitt. In it she concentrates on two fields where she has made seminal contributions: the automatic classification of white blood cells by video-based image microscopic systems, and computerized tomagraphic reconstruction (CAT Scanning). As noted, about 300 million blood smears are read annually in the United States at a cost of about 1.5 billion dollars. Such volume leads to manual errors which have implications on the everyday working of the clinician. Therefore much work has been done over the last 20 years to develop an automated detection system able to perform differential counting and other blood cytological tasks. Several such commercial machines are now on the market. Dr. Prewitt discusses the major problems of image articulation, image description, feature selection for discrimination, and statistical classification. She takes a case-study approach, showing how she and her coworkers developed their scheme. The techniques described are applicable to many other problems, as MATHEMATICAL
BIOSCIENCES
75:139-140
(1985)
139
OElsevier Science Publishing Co., Inc., 1985 52 Vanderbilt Ave., New York, NY 10017
0025-5564/85/$03.30
BOOK REVIEW
140
attested to by the current explosion of literature. One minor criticism is that the bibliography is almost exclusively made up of her own work, perhaps misleading the reader to believe that it is not an active field. Also, in addition to medical diagnosis, image analysis is now leading the way to basic biological discoveries
VI. The CAT reconstruction problem is of profound medical importance that affects numerous patients. Various algorithms are reviewed and future developments are outlined. Of course, the future is now past and even as Dr. Prewitt notes in a 1980 postscript, the field is rapidly developing. Today medical imaging is expanding and many new technologies are emerging, each of which requires mathematical analysis (ultrasound, whole body NMR, etc.) [2]. The section on mathematical and statistical models in physiopathology contains one review paper on mathematical oncology and four specific application papers. Upon reading this section the reader might get the impression that most modeling in medicine must be statistical in nature (an opinion that many modelers also hold). However, although medical data must be noisy by its very nature, there is a definite role for deterministic modeling in medicine and biology. In fact, one can argue that because many systems in biology are designed to compensate for random inputs, such stochastic effects are controlled for, thus allowing successful deterministic modeling. The articles in the section on medical diagnosis mainly use statistical decision theoretical approaches to diagnose various diseases. Today such endeavors are usually approached via expert systems: a group of rules and reasoning capable of simulating the decision strategy of the clinician. Such shining stars as MYCIN and INTERNIST have shown the usefulness of the technology [3]. The last section deals with health service delivery (except for the paper on optimal scheduling of cancer radiotherapy, which should rightly be in the modeling section, and which is an excellent treatment of the subject). The need for modeling to determine optimal allocation of health care resources has been emphasized in recent years by the skyrocketing costs of medical treatment. The papers presented here take a step in this direction. Such forward-looking modeling is needed, however this reviewer is not aware of a conserted modeling effort in this field. All in all, the papers in this book will provide both the neophyte and expert with some food for thought. Because of its low price, I think is deserves to be on the library shelf. The review of image analysis, although limited, is itself worth the cost. REFERENCES [l] [2] [3]
C. Nicolini, Ed., Cell Growth Plenum Press, 1982. For a mathematical introduction into some of the newer technologies, see Albert Macovski, Medical Imaging Sysrem, Prentice-Hall, 1983. A. Barr and E. Feigenbaum, Eds. The Handbook of Artificial Intelligence, Vol. II, William Kaufmann, Inc. 1982.
STANLEY ZIETZ Departments of Mathematics and Computer Science and Biomedical Sciences and Engineering Institute Drexel University Philadelphia, Pennsylvania 19104