Open Heart

Determinants of systolic murmurs without significant valvular heart disease in an unselected Norwegian adult population: the Tromsø Study

Background Systolic murmurs are common in adults without significant valvular heart disease (VHD) and are more prevalent in ...
Pulmonology Advisor

Men With Long COVID Exhibit Higher Rates of In-Hospital Mortality, CV Risk

Among adults with long COVID, male sex is linked to higher rates of in-hospital mortality and more cardiovascular complications.
Visual Studio Magazine

AdaBoost.R2 Regression Using C#

AdaBoost.R2 regression is a machine learning technique used to predict a single numeric value. AdaBoost.R2 builds a sequence of decision tree regressors where each accepted tree improves prediction ...
Scientific Research Publishing

Tranmer, M. and Elliot, M. (2008) Binary Logistic Regression. Cathie Marsh for Census and Survey Research Paper 20.

ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
Nature

Enhancing logistic regression classification: insights from simulation and real-world applications through ranked set sampling

Machine learning algorithms are widely used for disease prediction, but the choice of sampling method is a factor that affects model performance, particularly in large populations, limitations on the ...
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 ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
LinkedIn

Understanding Logistic Regression: Why It’s Still Called Regression

Logistic Regression is one of the most widely used algorithms in machine learning, especially when it comes to solving classification problems. Yet, its name often confuses beginners: why is it called ...
Frontiers

Multidimensional factors of depressive symptoms among Chinese undergraduate students: a cross-sectional study using binary logistic regression

This cross-sectional study investigates the interplay of lifestyle, behavioral, and psychosocial factors in predicting depressive symptoms among Chinese college students (N=508) using binary logistic ...
Nature

Farmers willingness to participate in integrated watershed management practice in North West Ethiopia using logistic regression model approach

Ethiopia is among the most at-risk countries due to the depletion of natural resources caused by soil erosion, deforestation, environmental degradation, recurring water shortages, and recurrent ...
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 ...