Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

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) ...
IEEE

Gender Classification Based on Machine Learning Models

Abstract: Automatic gender categorization has become an increasingly significant area in computer vision, with several applications. Gender equality is nowadays a keyword for today's scenario. This ...
IEEE

Severity Classification of Freezing of Gait Using Machine-Learning Algorithms: A Hidden State Model Approach

Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...
Fox News

Compact machine turns air into ready-to-use gasoline

Recently, Aircela, a fuel company headquartered in New York, publicly demonstrated a machine in Manhattan that produces gasoline directly from air. The event attracted city and state officials, ...
Frontiers

Construction and clinical visualization application of a predictive model for mortality risk in sepsis patients based on an improved machine learning model

Objective: To explore the construction and clinical visualization application of a mortality risk prediction model for sepsis patients based on an improved machine learning model. Methods: This ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...