Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

New research decodes hidden bias in health care LLMs

Artificial intelligence is increasingly used as a tool in many health care settings, from writing physicians' notes to making ...

How Recommender Systems Like Google Discover May Work

Google Discover is largely a mystery to publishers and the search marketing community even though Google has published ...
Frontiers

Advancing Deep Learning Frameworks for Enhanced Cervical Cancer Diagnosis, Staging and Treatment

Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...

NotebookLM helped me avoid decision fatigue — without juggling multiple tabs

If you want to work with the comparison outside NotebookLM, you can export any data table straight to Google Sheets. Just ...
InfoQ

MIT's Recursive Language Models Improve Performance on Long-Context Tasks

Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance ...
Tech Xplore

Benchmarking framework reveals major safety risks of using AI in lab experiments

While artificial intelligence (AI) models have proved useful in some areas of science, like predicting 3D protein structures, ...

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Scientific Research Publishing

Implementing an Electrocardiogram Suite in the Emergency Department to Decrease Door-to-EKG Time ()

Implementing an Electrocardiogram Suite in the Emergency Department to Decrease Door-to-EKG Time ...
IEEE

Label Feature Co-Learning for Facial and EEG Emotion Recognition

Abstract: Recognizing human emotions through behavioral and physiological signals is fundamental to overall health. However, since emotion occurs transiently, a semantics mismatch exists between the ...
IEEE

A Nearly Hamiltonian Neural Network-Enhanced Multi-Machine Power System Excitation Control

Abstract: The generalized Hamiltonian system theory (GHST) is a powerful tool for excitation control in high-dimensional non-linear power systems, but relies on reduced-order dynamics, given the ...