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AI-Powered Bayesian Statistics in Biomedicine
Statistics and artificial intelligence (AI) are distinct yet closely interconnected disciplines, each characterized by its own historical roots and...
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A synthetic likelihood approach for intractable markov random fields
We propose a new scalable method to approximate the intractable likelihood of the Potts model. The method decomposes the original likelihood into...
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Glomerulosclerosis detection with pre-trained CNNs ensemble
Glomerulosclerosis characterizes many conditions of primary kidney disease in advanced stages. Its accurate diagnosis relies on histological analysis...
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Mixture cure rate models with neural network estimated nonparametric components
Survival data including potentially cured subjects are common in clinical studies and mixture cure rate models are often used for analysis. The...
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Centers Participating in Multicenter Trials
Successful conduct of multicenter trials requires many different types of activities, implemented by different types of centers. Resource centers are...
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Key Variables Ascertainment and Validation in RW Setting
Ascertainment of key variables is a major component in the FDA Real-World Evidence (RWE) framework (FDA. Framework for FDA’s real-world evidence...
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De-identifying Clinical Trial Data
Conducting clinical trials involves collecting detailed health information about participants. Privacy of individual participants is important and...
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De-identifying Clinical Trial Data
Conducting clinical trials involves collecting detailed health information about participants. Privacy of individual participants is important and...
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Topological Object Data Analysis Methods with an Application to Medical Imaging
We apply ideas from algebraic topology to study distributions on object spaces. We present a framework for using persistence landscapes to vectorize...
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Centers Participating in Multicenter Trials
Successful conduct of multicenter trials requires many different types of activities, implemented by different types of centers. Resource centers are...
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Bridging Density Functional Theory and Big Data Analytics with Applications
The framework of the density functional theory (DFT) reveals both strong suitability and compatibility for investigating large-scale systems in the...
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Basic Statistics
In this chapter, we focus on some basic examples in Probability and Statistics. We phrase these concepts using the language and definitions we have...
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A Survey on Model-Based Co-Clustering: High Dimension and Estimation Challenges
Model-based co-clustering can be seen as a particularly important extension of model-based clustering. It allows for a significant reduction of both...
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Introduction
This chapter is an introduction to this Lecture Note. We briefly describe the contents of this book. Both parts are introduced, namely part A which...
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Suboptimal Comparison of Partitions
The distinction between classification and clustering is often based on a priori knowledge of classification labels. However, in the purely...
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Possible Clinical Use of Big Data: Personal Brain Connectomics
The biggest data is brain imaging data, which waited for clinical use during the last three decades. Topographic data interpretation prevailed for...
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Mammogram Diagnostics Using Robust Wavelet-Based Estimator of Hurst Exponent
Breast cancer is one of the leading causes of death in women. Mammography is an effective method for early detection of breast cancer. Like other...
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Integral transform methods in goodness-of-fit testing, II: the Wishart distributions
We initiate the study of goodness-of-fit testing for data consisting of positive definite matrices. Motivated by the appearance of positive definite...
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Logistic Regression Modeling on Mass Spectrometry Data in Proteomics Case-Control Discriminant Studies
We present an adaption of the logistic regression model for the evaluation of mass spectrometry data in proteomics case-control studies. We...