Objective To characterise the age-related impact of organ damage patterns on health-related quality of life (HRQoL) in ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Background/purpose Social media (SM) has become an indispensable tool in healthcare, providing platforms for networking and ...

A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how ...

Ripples maintain time-locked occurrence across the septo-temporal axis and hemispheres while showing local phase coupling, revealing a dual mode of synchrony in CA1 network dynamics.

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern some of the most complex dynamics found in nature and technology.

This new AI acts like a digital scientist, turning messy data into simple rules that explain how the world really works.

The development of glmSMA represents a valuable advancement in spatial transcriptomics analysis, offering a mathematically robust regression-based approach that achieves higher-resolution mapping of ...

Background Prior work suggests different interstitial lung diseases (ILDs) that share the radiological usual interstitial pneumonia (UIP) pattern have an overall worse prognosis. However, ...

Good sleep patterns are vital as the brain flushes toxins while asleep Getty A study found that poor sleep can negatively impact how well the glymphatic system works The system works by collecting ...