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

Phytochemicals are bioactive compounds derived from plants, such as flavonoids, alkaloids and ginsenosides. They are key ...

A leakage-aware evaluation of explainable machine learning found modest prediction of nanoparticle tumor delivery, with errors increasing for unseen materials and little transportability across ...

When machine learning models deliver problematic results, it can often happen in ways that humans can't make sense of, and this becomes dangerous when there are no limitations of the model, ...

Engineers can 3D-print high-performance titanium parts for aircraft, medical implants and advanced machinery, but finding the ...

In this paper, explainable artificial intelligence (XAI) based prediction is used for gate all around (GAA) MOSFET to predict its electrical behaviour. The data set is produced using TCAD simulations ...

As artificial intelligence usage continues to increase, there’s a problem lurking in the background growing larger by the day: It’s the ability of AI to explain itself so it’s clear what led to an ...

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The black box conundrum is one of the biggest roadblocks that can prevent banks from executing their AI strategies. Machine learning (ML) models tasked with identifying patterns in data, making ...

Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence–Based Prognosis for Patients With Advanced Solid Tumors Consecutive inpatients who underwent ...

While the idea of a black box is intriguing, it can miss the point. Placing information into a black box that spits out a solution is valuable but understanding what’s going on in that black box is ...