Abstract: To improve the performance of English-text classification, text classification systems aim to design appropriate algorithms for extracting features and auto-classifying texts with automatic ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...

As we approach the AI Impact Summit 2026, global AI exosystems are undergoing a brutal yet necessary recalibration. Those calibrations are driven by t.

Researchers claim that leading image editing AIs can be jailbroken through rasterized text and visual cues, allowing prohibited edits to bypass safety filters and succeed in up to 80.9% of cases.

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Kennesaw State University (KSU) is stepping into the future of workforce-ready education with the launch of a new Bachelor’s degree ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

After Valve announced its upcoming Steam Machine living room box earlier this month, some analysts suggested to Ars that Valve could and should aggressively subsidize that hardware with “loss leader” ...

With artificial intelligence now playing a major role in writing, communication, and content production, a growing number of organizations, from universities to hiring agencies, are turning to AI ...

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...