Author: Nada Lavrač
Publisher: Springer Science & Business Media
ISBN: 1461560594
Category : Computers
Languages : en
Pages : 320
Book Description
Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice.
Intelligent Data Analysis in Medicine and Pharmacology
Author: Nada Lavrač
Publisher: Springer Science & Business Media
ISBN: 1461560594
Category : Computers
Languages : en
Pages : 320
Book Description
Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice.
Publisher: Springer Science & Business Media
ISBN: 1461560594
Category : Computers
Languages : en
Pages : 320
Book Description
Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice.
Medical Applications of Intelligent Data Analysis: Research Advancements
Author: Magdalena-Benedito, Rafael
Publisher: IGI Global
ISBN: 1466618043
Category : Computers
Languages : en
Pages : 386
Book Description
"This book explores the potential of utilizing medical data through the implementation of developed models in practical applications"--Provided by publisher.
Publisher: IGI Global
ISBN: 1466618043
Category : Computers
Languages : en
Pages : 386
Book Description
"This book explores the potential of utilizing medical data through the implementation of developed models in practical applications"--Provided by publisher.
Medical Data Analysis
Author: Rüdiger W. Brause
Publisher: Springer
ISBN: 3540399496
Category : Computers
Languages : en
Pages : 327
Book Description
It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zing patient data, even in smaller health care institutions, the need for a rational treatment of all these data emerged as well. Therefore, the need for data exchange and presentation systems grew also. The goal of the symposium is to collect all these relevant aspects together. It provides an international forum for the sharing and exchange of original re- arch results, ideas and practical experiences among researchers and application developers from di erent areas related to medical applications dealing with the analysis of medical data. After a thorough reviewing process, 33 high quality papers were selected from the 45 international submissions. These contributions provided the di erent - pects of the eld in order to represent us with an exciting program.
Publisher: Springer
ISBN: 3540399496
Category : Computers
Languages : en
Pages : 327
Book Description
It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zing patient data, even in smaller health care institutions, the need for a rational treatment of all these data emerged as well. Therefore, the need for data exchange and presentation systems grew also. The goal of the symposium is to collect all these relevant aspects together. It provides an international forum for the sharing and exchange of original re- arch results, ideas and practical experiences among researchers and application developers from di erent areas related to medical applications dealing with the analysis of medical data. After a thorough reviewing process, 33 high quality papers were selected from the 45 international submissions. These contributions provided the di erent - pects of the eld in order to represent us with an exciting program.
MEDINFO 2001
Author: Vimla L. Patel
Publisher: IOS Press
ISBN: 9781586031947
Category : Medical
Languages : en
Pages : 724
Book Description
Technological infrastructure - Standards for interworking - Human-computer interaction - Knowledge representation - Information management - Decision support - Electronic patient records - Health information systems - Patient care aspects/telematics.
Publisher: IOS Press
ISBN: 9781586031947
Category : Medical
Languages : en
Pages : 724
Book Description
Technological infrastructure - Standards for interworking - Human-computer interaction - Knowledge representation - Information management - Decision support - Electronic patient records - Health information systems - Patient care aspects/telematics.
Biological and Medical Data Analysis
Author: José María Barreiro
Publisher: Springer Science & Business Media
ISBN: 3540239642
Category : Computers
Languages : en
Pages : 519
Book Description
This book constitutes the refereed proceedings of the 5th International Symposium on Biological and Medical Data Analysis, ISBMDA 2004, held in Barcelona, Spain in November 2004. The 50 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on data analysis for image processing, data visualization, decision support systems, information retrieval, knowledge discovery and data mining, statistical methods and tools, time series analysis, data management and analysis in bioinformatics, integration of biological and medical data, metabolic data and pathways, and microarray data analysis and visualization.
Publisher: Springer Science & Business Media
ISBN: 3540239642
Category : Computers
Languages : en
Pages : 519
Book Description
This book constitutes the refereed proceedings of the 5th International Symposium on Biological and Medical Data Analysis, ISBMDA 2004, held in Barcelona, Spain in November 2004. The 50 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on data analysis for image processing, data visualization, decision support systems, information retrieval, knowledge discovery and data mining, statistical methods and tools, time series analysis, data management and analysis in bioinformatics, integration of biological and medical data, metabolic data and pathways, and microarray data analysis and visualization.
Intelligent Data Analysis
Author: Deepak Gupta
Publisher: John Wiley & Sons
ISBN: 1119544459
Category : Technology & Engineering
Languages : en
Pages : 428
Book Description
This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.
Publisher: John Wiley & Sons
ISBN: 1119544459
Category : Technology & Engineering
Languages : en
Pages : 428
Book Description
This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.
Guide to Intelligent Data Analysis
Author: Michael R. Berthold
Publisher: Springer Science & Business Media
ISBN: 184882260X
Category : Computers
Languages : en
Pages : 399
Book Description
Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examples to support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
Publisher: Springer Science & Business Media
ISBN: 184882260X
Category : Computers
Languages : en
Pages : 399
Book Description
Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examples to support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
Artificial Intelligence in Medicine
Author: Werner Horn
Publisher: Springer Science & Business Media
ISBN: 354066162X
Category : Medical
Languages : en
Pages : 447
Book Description
This book constitutes the refereed proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, held in Aalborg, Denmark, in June 1999. The 27 full papers and 19 short papers presented in the book together with four invited papers were selected from 90 submissions. The papers are organized in topical sections on guidelines and protocols; decision support systems, knowledge-based systems, and cooperative systems; model-based systems; neural nets and causal probabilistic networks; knowledge representation; temporal reasoning; machine learning; natural language processing; and image processing and computer aided design.
Publisher: Springer Science & Business Media
ISBN: 354066162X
Category : Medical
Languages : en
Pages : 447
Book Description
This book constitutes the refereed proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, held in Aalborg, Denmark, in June 1999. The 27 full papers and 19 short papers presented in the book together with four invited papers were selected from 90 submissions. The papers are organized in topical sections on guidelines and protocols; decision support systems, knowledge-based systems, and cooperative systems; model-based systems; neural nets and causal probabilistic networks; knowledge representation; temporal reasoning; machine learning; natural language processing; and image processing and computer aided design.
9789815223026
Author: Dilpreet Singh, Prashant Tiwari
Publisher: Bentham Science Publishers
ISBN: 981522302X
Category : Science
Languages : en
Pages : 339
Book Description
Software and Programming Tools in Pharmaceutical Research is a detailed primer on the use for computer programs in the design and development of new drugs. Chapters offer information about different programs and computational techniques in pharmacology. The book will help readers to harness computer technologies in pharmaceutical investigations. Readers will also appreciate the pivotal role that software applications and programming tools play in revolutionizing the pharmaceutical industry. The book includes nine structured chapters, each addressing a critical aspect of pharmaceutical research and software utilization. From an introduction to pharmaceutical informatics and computational chemistry to advanced topics like molecular modeling, data mining, and high-throughput screening, this book covers a wide range of topics. Key Features: · Practical Insights: Presents practical knowledge on how to effectively utilize software tools in pharmaceutical research. · Interdisciplinary Approach: Bridges the gap between pharmaceutical science and computer science · Cutting-Edge Topics: Covers the latest advancements in computational drug development, including data analysis and visualization techniques, drug repurposing, pharmacokinetic modelling and screening. · Recommendations for Tools: Includes informative tables for software tools · Referenced content: Includes scientific references for advanced readers The book is an ideal primer for students and educators in pharmaceutical science and computational biology, providing a comprehensive foundation for this rapidly evolving field. It is also an essential resource for pharmaceutical researchers, scientists, and professionals looking to enhance their understanding of software tools and programming in drug development.
Publisher: Bentham Science Publishers
ISBN: 981522302X
Category : Science
Languages : en
Pages : 339
Book Description
Software and Programming Tools in Pharmaceutical Research is a detailed primer on the use for computer programs in the design and development of new drugs. Chapters offer information about different programs and computational techniques in pharmacology. The book will help readers to harness computer technologies in pharmaceutical investigations. Readers will also appreciate the pivotal role that software applications and programming tools play in revolutionizing the pharmaceutical industry. The book includes nine structured chapters, each addressing a critical aspect of pharmaceutical research and software utilization. From an introduction to pharmaceutical informatics and computational chemistry to advanced topics like molecular modeling, data mining, and high-throughput screening, this book covers a wide range of topics. Key Features: · Practical Insights: Presents practical knowledge on how to effectively utilize software tools in pharmaceutical research. · Interdisciplinary Approach: Bridges the gap between pharmaceutical science and computer science · Cutting-Edge Topics: Covers the latest advancements in computational drug development, including data analysis and visualization techniques, drug repurposing, pharmacokinetic modelling and screening. · Recommendations for Tools: Includes informative tables for software tools · Referenced content: Includes scientific references for advanced readers The book is an ideal primer for students and educators in pharmaceutical science and computational biology, providing a comprehensive foundation for this rapidly evolving field. It is also an essential resource for pharmaceutical researchers, scientists, and professionals looking to enhance their understanding of software tools and programming in drug development.
Artificial Intelligence in Medicine
Author: Silvana Quaglini
Publisher: Springer
ISBN: 3540482296
Category : Computers
Languages : en
Pages : 484
Book Description
This book constitutes the refereed proceedings of the 8th Conference on Artificial Intelligence in Medicine in Europe, AIME 2001, held in Cascais, Portugal in July 2001. The 31 revised full papers presented together with 30 posters and two invited papers were carefully reviewed and selected from 79 submissions. Among the topics addressed in their context on medical information processing are knowledge management, machine learning, data mining, decision support systems, temporal reasoning, case-based reasoning, planning and scheduling, natural language processing, computer vision, image and signal interpretation, intelligent agents, telemedicine, careflow systems, and cognitive modeling.
Publisher: Springer
ISBN: 3540482296
Category : Computers
Languages : en
Pages : 484
Book Description
This book constitutes the refereed proceedings of the 8th Conference on Artificial Intelligence in Medicine in Europe, AIME 2001, held in Cascais, Portugal in July 2001. The 31 revised full papers presented together with 30 posters and two invited papers were carefully reviewed and selected from 79 submissions. Among the topics addressed in their context on medical information processing are knowledge management, machine learning, data mining, decision support systems, temporal reasoning, case-based reasoning, planning and scheduling, natural language processing, computer vision, image and signal interpretation, intelligent agents, telemedicine, careflow systems, and cognitive modeling.