Encyclopaedia of Biostatistics, Bioinformatics and Computer Applications
Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. Biostatistical reasoning and modelling were of critical importance to the foundation theories of modern biology. ln larger universities where both a statistics and a biostatistics department exist, the degree of integration between the two departments may range from the bare minimum to very close collaboration. ln general, the difference between a statistics program and a biostatistics one is twofold: (i) statistics departments will often host theoretical/methodological research which arc less common in biostatistics programs and (ii) statistics departments have lines of research that may include biomedical applications but also other areas such as industry (quality control), business and economics and biological areas other than medicine. Applications for machine learning include machine perception, computer vision, natural language processing, syntactic pattern recognition, search engines, medical diagnosis, bioinformatics, brain-machine interfaces and cheminformatics, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, object recognition in computer vision, game playing, software engineering, adaptive websites, robot locomotion, and structural health monitoring. This book provides deep insight to various dimensions of issues relating to development of this subject.
1138747969
Encyclopaedia of Biostatistics, Bioinformatics and Computer Applications
Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. Biostatistical reasoning and modelling were of critical importance to the foundation theories of modern biology. ln larger universities where both a statistics and a biostatistics department exist, the degree of integration between the two departments may range from the bare minimum to very close collaboration. ln general, the difference between a statistics program and a biostatistics one is twofold: (i) statistics departments will often host theoretical/methodological research which arc less common in biostatistics programs and (ii) statistics departments have lines of research that may include biomedical applications but also other areas such as industry (quality control), business and economics and biological areas other than medicine. Applications for machine learning include machine perception, computer vision, natural language processing, syntactic pattern recognition, search engines, medical diagnosis, bioinformatics, brain-machine interfaces and cheminformatics, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, object recognition in computer vision, game playing, software engineering, adaptive websites, robot locomotion, and structural health monitoring. This book provides deep insight to various dimensions of issues relating to development of this subject.
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Encyclopaedia of Biostatistics, Bioinformatics and Computer Applications

Encyclopaedia of Biostatistics, Bioinformatics and Computer Applications

by Rajneesh Narayan
Encyclopaedia of Biostatistics, Bioinformatics and Computer Applications

Encyclopaedia of Biostatistics, Bioinformatics and Computer Applications

by Rajneesh Narayan

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Overview

Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results. Biostatistical reasoning and modelling were of critical importance to the foundation theories of modern biology. ln larger universities where both a statistics and a biostatistics department exist, the degree of integration between the two departments may range from the bare minimum to very close collaboration. ln general, the difference between a statistics program and a biostatistics one is twofold: (i) statistics departments will often host theoretical/methodological research which arc less common in biostatistics programs and (ii) statistics departments have lines of research that may include biomedical applications but also other areas such as industry (quality control), business and economics and biological areas other than medicine. Applications for machine learning include machine perception, computer vision, natural language processing, syntactic pattern recognition, search engines, medical diagnosis, bioinformatics, brain-machine interfaces and cheminformatics, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, object recognition in computer vision, game playing, software engineering, adaptive websites, robot locomotion, and structural health monitoring. This book provides deep insight to various dimensions of issues relating to development of this subject.

Product Details

ISBN-13: 9789354114991
Publisher: Anmol Publications PVT. LTD.
Publication date: 06/30/2011
Sold by: Barnes & Noble
Format: eBook
Pages: 304
File size: 833 KB

About the Author

Rajneesh Narayan has a 5 years industry and 2 years teaching experience in areas of Computing. He has teaching, research. and consulting experience in business computing. He has published many articles in national and international journals. At present he is visiting faculty in Indira Gandhi National Open University, New Delhi.
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