RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
BMJ Open

Outcomes of open abdominal surgery at a single-centre tertiary referral hospital in Tanzania: a prospective, observational, single-arm cohort study

Objectives To assess the outcomes of patients undergoing open abdominal surgery at a National Referral Hospital in Tanzania. Design A prospective, observational, single-arm cohort study. Setting Dar ...
The New York Times

Nature Is Still Molding Human Genes, Study Finds

Some researchers hold that evolution hasn’t much altered humans in the past 10,000 years. A new analysis of ancient DNA indicates that natural selection continued to shape hundreds of genes. By Carl ...
SciELO

Comparison of supervised machine learning and variable selection methods for body weight prediction of growth pigs using image processing data

This research aimed to compare statistical methods (random forest, RIDGE, LASSO, and elastic net regression) for the prediction of body weight in purebred and crossbred pigs reared in Brazil. This ...
IEEE

Fault-Influenced Variable Selection and Distributional Offset Evaluation of CVDs Graph Convolutional Neural Network for Nonlinear KPI-Related Process Monitoring

Abstract: The majority of fault diagnosis techniques for root cause identification often overlook a critical aspect of complex industrial operations, which is reflected in the neutralization and ...
Scientific Research Publishing

Wang, X., Jiang, Y., Huang, M. and Zhang, H. (2013) Robust Variable Selection with Exponential Squared Loss. Journal of the American Statistical Association, 108, 632-643.

ABSTRACT: Function-on-scalar regression is a type of function response regression used to analyze the relationship between function response and a set of scalar predictor factors. The variable ...
IEEE

Sparse Variable Selection on High Dimensional Heterogeneous Data With Tree Structured Responses

Abstract: We consider the problem of sparse variable selection on high dimension heterogeneous data sets, which has been taking on renewed interest recently due to the growth of biological and medical ...
Frontiers

Variable Selection in Chemometrics

Since its emergence, chemometrics has been based essentially on factorial methods, whose aim is to extract meaningful directions in the space of the measured variables, called latent variables, or ...