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.
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 ...
C&EN

Alumina-Supported Catalyst Development for Propane Dehydrogenation via Interpretable Machine Learning and Experimental Validation

State Key Laboratory of Fine Chemicals, Liaoning Key Laboratory for Catalytic Conversion of Carbon Resources, School of Chemistry, School of Chemical Engineering, Dalian University of Technology, ...
IEEE

Performance Comparison of Machine Learning Classifiers for Change Detection on Satellite Data

Abstract: The proliferation of remotely sensed satellite data has significantly enhanced research in the field of Land Use and Land Cover (LULC) analysis. LULC analysis plays a crucial role in ...
Frontiers

Identification of routine blood derived hematological and lipid indices in ILD through machine learning; a retrospective case-control study

Introduction: Interstitial lung disease (ILD) comprises various disorders marked by pulmonary inflammation and fibrosis. Early diagnosis and risk prediction are vital for improving patient outcomes.
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, ...