Moving past speculation: How deterministic CPUs deliver predictable AI performance

As David Patterson observed in 1980, “A RISC potentially gains in speed merely from a simpler design.” Patterson’s principle of simplicity underpins a new alternative to speculation: A deterministic, ...

AI Is Teaching the Next Generation of M.B.A.s the Classic Case Study

Business students at Northwestern aren’t using AI to shortcut their way through assignments. It’s helping them problem-solve real strategic challenges.

Large Language Models Get All the Hype, but Small Models Do the Real Work

For many tasks in corporate America, it’s not the biggest and smartest AI models, but the smaller, more simplistic ones that are winning the day.
Harvard Business Review

When Working With AI, Act Like a Decision-Maker—Not a Tool-User

While AI can create space for higher-order thinking, it can also tempt us to outsource that thinking altogether. Good ...
ahajournals.org

Claims‐Based Machine Learning Classifier of Modified Rankin Scale in Acute Ischemic Stroke

We developed a classifier to infer acute ischemic stroke severity from Medicare claims using the modified Rankin Scale at discharge. The classifier can be used to improve stroke outcomes research and ...
ahajournals.org

Abstract Wed136: Integration of Mechanistic Fontan Circulatory Models with Interpretable Machine Learning Classifiers

Abstract Wed136: Integration of Mechanistic Fontan Circulatory Models with Interpretable Machine Learning Classifiers Noah Schenk, BS, Alexander Egbe, MD, MPH, Brian Carlson, PhD, and Daniel Beard, ...
GEN

Fentanyl-Hunter: Machine Learning–Driven Screening for Opioid Metabolites

Fentanyl, a widely used synthetic opioid, can be fatal even at low exposures, and in recent years, the illegal abuse of fentanyl and its analogs has become a serious global concern. Scientists headed ...
Frontiers

Machine learning pipeline for microparticle size classification in self-mixing interferometric signals for flow cytometry

Self-mixing interferometry (SMI) is an emerging optical sensing technique for detecting and classifying microparticles in non-contact and label-free flowmetry applications. High precision and ...
IEEE

Accurate and Efficient Fluid Flow Regime Classification Using Localized Texture Descriptors and Machine Learning

Abstract: This paper presents an image-based framework for classifying fluid flow regimes into low and high-speed states by utilizing spatially localized texture features combined with machine ...
IEEE

Bringing Machine Learning Classifiers Into Critical Cyber-Physical Systems: A Matter of Design

Machine Learning (ML) models are increasingly used by domain experts to tackle classification tasks, aiming for high predictive accuracy. However, classifiers are inherently prone to ...