While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

People living with HIV who have taken highly active antiretroviral therapy can have hyperlipidemia predicted in advance by ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

Superhydrides are materials that can store significantly more hydrogen than conventional hydrides and present a highly ...

Early prediction of in-hospital pneumonia mortality can effectively be done using a machine learning (ML) model based on clinical data.

PanGIA’s test approach pairs proprietary chemistry with machine learning to detect cancer-specific biosignatures from urine ...

In my opinion, the future belongs instead to hyperspecialized AI models that are tailored to excel in hyper-specific domains.

Unlike existing models that rely on expensive or infrequently collected data, BloomSense uses a cost-effective sensor ...

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, ...

In livestock, veterinary drug residues are detected through non-destructive methods like hyperspectral imaging. One case in ...

Chronic pain conditions, long-lasting medical conditions characterized by persistent pain in specific areas of the body, are ...