A new framework called ESACRIF integrates survival analysis, explainable AI, counterfactual reasoning and profit-aware ...

Finnish researchers have built an explainable machine learning framework that segments B2B customers, predicts purchases with ...

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, ...

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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 ...

Systematic mapping of gender disparities in oncology publications of north African countries: The GEORGiNA study. This is an ASCO Meeting Abstract from the ASCO Breakthrough: A Global Summit for ...

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

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 ...

In the realm of Intensive Outpatient Programs (IOP), machine learning is reshaping how facilities such as those in Scottsdale operate. By integrating advanced ...

Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...