This study presents a non-invasive approach to detect anxiety and depression through gait analysis and machine learning, ...

Mass. maternal health researchers want to expedite the detection of postpartum depression risk, starting in the delivery room after the baby is born.

Their study – “ Depression Detection Using Digital Traces on Social Media: A Knowledge-aware Deep Learning Approach ” – was published by the Journal of Management Information Systems and focuses on ...

While AI models hold promise for such predictions, the development of deep learning models capable of reliably forecasting GPCR ligands with defined bioactivities remains challenging, largely due to ...

Abstract Diabetic retinopathy (DR), a leading cause of vision impairment worldwide, primarily impacts individuals with diabetes, making early detection vital to prevent irreversible vision loss.

Advanced driving assistance integration in electric motorcycles: road surface classification with a focus on gravel detection using deep learning ...

Study in Npj Digital Medicine evaluates COMPOSER, a deep learning model for early sepsis prediction, showing its effectiveness in improving patient care and reducing in-hospital mortality rates.