Ergebnisse für: biomedical data analysis
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This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical infor...
This introductory book is a beginner-friendly resource that empowers you to harness Python programming for exploring and understanding biomedical data. In today’s data-driven world, the ability to analyze and interpret complex datasets is a vital skill—especially in biomedicine, where data-drive...
The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as w...
This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical infor...
This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical infor...
This introductory book is a beginner-friendly resource that empowers you to harness Python programming for exploring and understanding biomedical data. In today’s data-driven world, the ability to analyze and interpret complex datasets is a vital skill—especially in biomedicine, where data-drive...
The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as w...
The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as w...
This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled ‘Optimization and Data Analysis in Biomedical Informatics’ was organized at The Fields Institute. Following this event invited contributions were...
The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.
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Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB(r) toolbox for the collection, visualization, and evaluation of experimental and real-life data
Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB(r) pres...
This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled ‘Optimization and Data Analysis in Biomedical Informatics’ was organized at The Fields Institute. Following this event invited contributions were...
This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 11-12, 2010 a workshop entitled ‘Optimization and Data Analysis in Biomedical Informatics’ was organized at The Fields Institute. Following this event invited contributions were...
Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB® toolbox for the collection, visualization, and evaluation of experimental and real-life data
Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® presen...
The new edition adds a chapter on multiple linear regression inbiomedical research, with sections including the multiple linearregressions model and least squares; the ANOVA table, parameterestimates, and confidence intervals; partial f-tests; polynomialregression; and analysis of covariance.
* Orga...
Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB® toolbox for the collection, visualization, and evaluation of experimental and real-life data
Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® presen...
This volume constitutes the proceedings of the First International Workshop on Artificial Intelligence for Biomedical Data, AIBio 2025, held in Conjunction with the European Conference on Artificial Intelligence, ECAI 2025, in Bologna, Italy, during October 25–26, 2025.
The 12 full papers and 5 sh...
This volume constitutes the proceedings of the First International Workshop on Artificial Intelligence for Biomedical Data, AIBio 2025, held in Conjunction with the European Conference on Artificial Intelligence, ECAI 2025, in Bologna, Italy, during October 25–26, 2025.
The 12 full papers and 5 sh...
This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary...