The World Bank classification of low-income, middle-income, and high-income country groups, that uses gross national income per capita, shapes financing, research priorities, and political narratives.

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 ...

A wave of pseudoscientific papers has tried to dismantle one of biology’s most fundamental truths: only two sexes exist, male and female. These papers often claim that sex is a broad “spectrum,” and ...

Binary cross-entropy (BCE) is the default loss function for binary classification—but it breaks down badly on imbalanced datasets. The reason is subtle but important: BCE weighs mistakes from both ...

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 = ...

Abstract: Efficient and accurate small molecule classification methods can significantly improve the efficiency of scientific research and industrial applications, but in real scenarios, many datasets ...

i am running binary classification report. my "target" column is binary 0,1 values, "pred_lablel" is binary 01, values and "prediction" is probabilities between 0-1 i get auc/roc, log loss but ...

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...

Abstract: This study explores the use of a hybrid machine learning model that combines support vector machines (SVMs) and convolutional neural networks (CNNs) for the diagnosis of lung disorders in ...