Computational Methods in Biomedical Research

ISBN-13: 9780367388010 / Angielski / Miękka / 2019 / 432 str.

Ravindra Khattree; Dayanand Naik

Opis

Using real-world data from disease areas, such as cancer and HIV, this volume explores important computational statistical methods that are employed in biomedical research. It discusses microarray data analysis, machine learning techniques, and mass spectrometry-based protein profiling. The book also uses state space models to predict US cancer mortality rates and describes the application of multistate models to analyze multiple failure times. It covers various Bayesian techniques, the sequential monitoring of randomization tests, mixed-effects models, classification rules for repeated measures data, and estimation methods for analyzing longitudinal data.

Spis treści

Preface. Microarray Data Analysis. Machine Learning Techniques for Bioinformatics: Fundamentals and Applications. Machine Learning Methods for Cancer Diagnosis and Prognostication. Protein Profiling for Disease Proteomics with Mass Spectrometry: Computational Challenges. Predicting US Cancer Mortality Counts Using State Space Models. Analyzing Multiple Failure Time Data Using SAS^® Software. Mixed-Effects Models for Longitudinal Virologic and Immunologic HIV Data. Bayesian Computational Methods in Biomedical Research. Sequential Monitoring of Randomization Tests. Proportional Hazards Mixed-Effects Models and Applications. Classification Rules for Repeated Measures Data from Biomedical Research. Estimation Methods for Analyzing Longitudinal Data Occurring in Biomedical Research. Index.

O autorze

Ravindra Khattree, Dayanand N. Naik