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Biomathematics. Biometry. Biostatistics --- Mathematical statistics. --- Biometry.
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Biometry --- Methodology. --- Research.
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This book is organized into 4 sections, each looking at the question of outcome prediction in cancer from a different angle. The first section describes the clinical problem and some of the predicaments that clinicians face in dealing with cancer. Amongst issues discussed in this section are the TNM staging, accepted methods for survival analysis and competing risks. The second section describes the biological and genetic markers and the r̥le of bioinformatics. Understanding of the genetic and environmental basis of cancers will help in identifying high-risk populations and developing effective prevention and early detection strategies. The third section provides technical details of mathematical analysis behind survival prediction backed up by examples from various types of cancers. The fourth section describes a number of machine learning methods which have been applied to decision support in cancer. The final section describes how information is shared within the scientific and medical communities and with the general population using information technology and the World Wide Web. * Applications cover 8 types of cancer including brain, eye, mouth, head and neck, breast, lungs, colon and prostate * Include contributions from authors in 5 different disciplines * Provides a valuable educational tool for medical informatics.
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Biomathematics. Biometry. Biostatistics --- Human medicine --- Medical statistics.
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Mathematical statistics --- Failure time data analysis. --- Survival analysis (Biometry). --- Failure time data analysis --- Survival analysis (Biometry) --- 368.01 --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Analysis, Failure time data --- Data analysis, Failure time --- Biometry --- Failure analysis (Engineering) --- Competing risks
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Biomathematics. Biometry. Biostatistics --- Biomathematics --- Biomathématiques --- Congresses --- Congrès et conférences. --- Biomathématiques.
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Provides a coherent and comprehensive account of the theory and practice of real-time human disease outbreak detection, explicitly recognizing the revolution in practices of infection control and public health surveillance.*Reviews the current mathematical, statistical, and computer science systems for early detection of disease outbreaks*Provides extensive coverage of existing surveillance data*Discusses experimental methods for data measurement and evaluation*Addresses engineering and practical implementation of effective early detection systems*Includes real case stu
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Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researchers in evolutionary computation (EC) have turned their attention to these problems. They understand the power of EC to rapidly search very large and complex spaces and return reasonable solutions. While these researchers are increasingly interested in problems from the biological sciences, EC and its
Biomathematics. Biometry. Biostatistics --- Molecular biology --- Bioinformatics. --- Evolutionary computation.
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