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, ...

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 ...

In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

Every radiologist knows the frustration: the AI model that works brilliantly at one hospital can stumble badly at another.

Steatotic liver disease (SLD), formerly named fatty liver disease, has a prevalence estimated at 30–38% in adults. Detection of SLD is important, since prompt initiation of treatment can stop disease ...

Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights—including a model-estimated probability score for ...

Lung cancer (LC) is a leading cause of cancer-related mortality in the United States. Accurate prediction of LC mortality rates is crucial for guiding targeted interventions and addressing health ...

Creating machine learning models that generate accurate results is one thing, but it's quite another to ensure model interpretability -- the ability to understand why the ML models that power AI tools ...

Image courtesy by QUE.com The Paradigm Shift in Machine Learning Architectures As we move into 2026, the landscape of Machine Learning ...

Memes have become one of the most pervasive modes of communication on social media, blending images and text with humor, ...

Affirm Holdings, Inc. AFRM is launching a new transformer-based machine learning model for real-time credit underwriting at U.S. checkouts. The system analyzes the order and timing of events across a ...