BMJ Open

Psychological burden and its association with preferred form of psychological assistance of healthcare workers during the COVID-19 pandemic in China: a cross-sectional study

Objective This study focused on the preferences for psychological assistance and associated factors among Chinese healthcare workers (HCWs) during the COVID-19 pandemic. Design Cross-sectional ...
Lupus Science & Medicine

Serum S100A8 as a potential biomarker for diagnosis of antiphospholipid syndrome and risk stratification among aPL carriers

Background Current diagnosis of antiphospholipid syndrome (APS) relies on antiphospholipid antibodies (aPL) testing, but false-positive aPL results and asymptomatic aPL carriers pose significant ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
Yahoo

This Number System Beats Binary, But Most Computers Can’t Use It

Add Yahoo as a preferred source to see more of our stories on Google. The Babylonians used separate combinations of two symbols to represent every single number from 1 to 59. That sounds pretty ...
The New York Times

Everyone Is Using A.I. for Everything. Is That Bad?

Either way, let’s not be in denial about it. Credit...Illustration by Christoph Niemann Supported by By Kevin Roose and Casey Newton Kevin Roose and Casey Newton are the hosts of The Times’s “Hard ...
IEEE

Comparative Analysis of Sparse Multinomial Logistic Regression and Convolutional Neural Networks for Multi-Class Image Classification

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
Scientific Research Publishing

Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
Frontiers

Impact of using time-averaged exposure metrics on binary endpoints in exposure-response analyses

Exposure-response (ER) analyses are routinely performed in drug development to evaluate the risk-to-benefit ratio, primarily to inform decisions around dose selection, justification, and confirmation ...
Visual Studio Magazine

Gradient Boosting Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the gradient boosting regression technique, where the goal is to predict a single numeric value. Compared to ...