Researchers propose a Holistic Explainable AI framework that embeds explanation into every stage of the data-analysis ...

Researchers trained an XGBoost machine learning model to estimate the residual tensile strength of artificially aged silk ...

Introduction: Why This Matters Now - Almost all commercial technology deals between a customer and platform provider now ...

Scientists at Rensselaer Polytechnic Institute (RPI) have developed an artificial intelligence model to streamline and improve screening for Parkinson's disease (PD) so doctors can refer patients for ...

"Which products will sell, and how many, next month?""How many hours will this task take?""Can we identify conditions prone to defects in advance?"In our work, there are times when we rely on past ...

All materials contain inherent defects. These are not always harmful, since they can be used to engineer and introduce ...

Developing reliable machine learning models for healthcare can be challenging when only small datasets are available. This challenge motivates research into whether quantum computing approaches can ...

Using admission data, a machine learning model detected patients with acute coronary syndrome at high-risk for cardiogenic ...

Introduction Recurrent stroke remains a major threat after an index stroke, but individual risk is difficult to estimate because recurrence reflects interacting clinical, imaging, treatment, ...

A trading system can generate buy or sell signals without revealing how it reached its decision. That opacity is central to ...