Predictive AI tools can enable early detection of intimate partner violence

Researchers at Mass General Brigham have developed a series of artificial intelligence (AI) tools that uses machine learning ...
News-Medical.Net

Machine learning model may provide an earning warning of preeclampsia in late gestation

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
Scientific Research Publishing

Cybersecurity and Forensic Audio Analysis: Deepfake Detection Based on Mfcc, Audio-Text Disconsistency, and Prosodic Features ()

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
IEEE

Predictive Analytics in Mental Health: Machine Learning Models for Major Depressive Disorder Detection using Sensor Data

Abstract: The recent integration of Machine Learning (ML) and sensor technologies in healthcare, particularly for diagnosing Major Depressive Disorder (MDD), has paved the way for advanced predictive ...
Analytics Insight

Top Data Science Projects to Boost Your Resume in 2026

Overview:Practical projects can help you showcase technical skill, programming knowledge, and business awareness during the hiring process.Designing end-to-end ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
IEEE

Applying Causal Machine Learning to Spatiotemporal Data Analysis: An Investigation of Opportunities and Challenges

Abstract: Traditional spatiotemporal data analysis often relies on predictive models that overlook causal relationships, making it difficult to identify true drivers and formulate effective ...