PromptSE uses structured LLM prompting to generate pharmacologically relevant side-effect representations, then feeds them ...

In a recent study published in The Lancet Digital Health, researchers performed a meta-analysis to evaluate the quality and performance of deep learning and machine learning models for long-term ...

The use of artificial intelligence in environmental control systems often centers on two contrasting approaches, static deep ...

Many U.S. hospitals using predictive models are not evaluating their tools internally for accuracy, and fewer still are evaluating them for potential biases, according to a study published in the most ...

Forbes contributors publish independent expert analyses and insights. David Henkin helps organizations and individuals innovate and grow. Predictive analytics has evolved from a niche discipline into ...

A Systematic Review of Adoption, Barriers and Strategic Implications and published in Administrative Sciences, reviewed 37 peer-reviewed studies from 2015 to 2025 and found that AI-driven demand ...

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...

A surprisingly easy way to multiply an AI model’s profit is to drive decisions via expected value instead of predictive scores. Here's how, illustrated with fraud detection.

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Automakers and repair shops are rapidly adopting AI-powered diagnostic systems that cut troubleshooting time, predict faults before breakdowns, and integrate with connected vehicle platforms. Advances ...