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 ...

This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...

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 ...

Scientists in Australia have developed an “explainable” artificial intelligence (AI) tool that could help doctors diagnose schizophrenia by analyzing brainwave patterns, AzerNEWS reports, citing ...

In a significant breakthrough, researchers have developed an advanced explainable deep learning model to predict and analyze harmful algal blooms (HABs) in freshwater lakes and reservoirs across China ...

A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes applications. By introducing ...

The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...

Shekar Vollem, a Senior Software Engineer, researcher, inventor, peer reviewer, and technology leader whose work spans ...

The actuarial methodology powering insurance risk models is advancing faster than most carriers realize. Here is what is ...

The terrestrial water cycle is a fundamental component of Earth's climate system, governing the exchange of water between land surfaces and the atmosphere.