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Found 7 papers, 1 papers with code
Changes from Classical Statistics to Modern Statistics and Data Science
We urgently need to shift the paradigm for data analysis from the classical Euclidean data analysis to both Euclidean and non Euclidean data analysis and develop more and more innovative methods for describing, estimating and inferring non Euclidean geometries of modern real datasets.
Artificial Intelligence Forecasting of Covid-19 in China
BACKGROUND An alternative to epidemiological models for transmission dynamics of Covid-19 in China, we propose the artificial intelligence (AI)-inspired methods for real-time forecasting of Covid-19 to estimate the size, lengths and ending time of Covid-19 across China.
A New Statistical Framework for Genetic Pleiotropic Analysis of High Dimensional Phenotype Data
The widely used genetic pleiotropic analysis of multiple phenotypes are often designed for examining the relationship between common variants and a few phenotypes.
Random Bits Regression: a Strong General Predictor for Big Data
To improve accuracy and speed of regressions and classifications, we present a data-based prediction method, Random Bits Regression (RBR).
A Novel Statistical Method Based on Dynamic Models for Classification
An essential issue for classifying dynamic and functional data is how to effectively reduce their dimension and explore dynamic feature.
Fully Automated Myocardial Infarction Classification using Ordinary Differential Equations
The estimated time varying coefficients of the second order ODE were used as an input to the support vector machine (SVM) for the MI classification.
Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis
The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis.
