Background Patients who consult their GP about psychological complaints, such as feeling anxious or depressed, are often ...
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 ...
Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
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 ...
Objectives: This study aimed to evaluate perceptions and practices of urologists in Saudi Arabia regarding discussions of erectile dysfunction (ED) and ejaculatory dysfunction (EjD) with patients ...
In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
In standard ER analyses, exposure metrics are derived using individual empirical Bayes estimates from a developed population pharmacokinetic (PopPK) model. For each subject, the PopPK model is then ...
To develop a machine learning model using logistic regression to predict the likelihood of cancer (e.g., benign or malignant) based on diagnostic data. Dataset: Utilized publicly available cancer ...
In this episode of eSpeaks, Jennifer Margles, Director of Product Management at BMC Software, discusses the transition from traditional job scheduling to the era of the autonomous enterprise. eSpeaks’ ...
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