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 ...

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 ...

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 ...

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

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 ...

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.

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

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 ...

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 ...