Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

This project focuses on building and evaluating machine learning (ML) classification models to predict whether a person has diabetes based on medical and demographic features. It was developed as an ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Abstract: The collaborative classification of dual-frequency polarimetric synthetic aperture radar (PolSAR) images is a meaningful but also challenging research. The effect of regional consistency on ...

A new ranking methodology places Barry Bonds over Babe Ruth as the game’s best player ever. Statisticians, at least, are cheering. By Alexander Nazaryan Every sport has its arguments over which player ...

This study was carried out to statistically evaluate the performance of the PHYGROW model in simulating the growth of corn and sorghum plants in different locations in the semi-arid region of Ceará ...

CREATING NEW NON-CAREER, POLICY-ORIENTED EMPLOYEES IN THE FEDERAL GOVERNMENT: Today, President Donald J. Trump signed an Executive Order creating a new classification of non-career federal workers, ...

Abstract: Assessing classification confidence is essential for effectively leveraging Large Language Models (LLMs) in automated data labeling, particularly within the sensitive contexts of ...

1 The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China 2 College of Information Engineering, Henan University of Science and ...

Background: Breast cancer is the most common malignant tumor in women worldwide, and early detection is crucial to improving patient prognosis. However, traditional ultrasound examinations rely ...