This valuable study uses naturalistic movie-viewing fMRI and stacked encoding models to investigate sensory feature representations in autistic and non-autistic youth, showing a relative shift toward ...

The Diagnostic Window Bottleneck: Neurologists rely heavily on EEGs to diagnose epilepsy, but standard clinical sessions provide only a 20-minute snapshot of brain activity, making manual detection ...

Objectives To determine the prevalence and clinical characteristics associated with polyneuropathy in kidney transplant ...

Purpose To evaluate the performance of swept source optical coherence tomography (SS-OCT) to detect gonioscopic angle closure using different classification algorithms. Methods This was a ...

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

Mount Sinai researchers have developed an AI-powered surgical training model that guided researchers through a complex kidney cancer procedure — with no human instructor present. All 17 trainees in ...

Abstract: In this study, we aim to develop a respiratory disease detection and classification model using machine learning techniques. Respiratory diseases are a significant global health problem, and ...

Abstract: We present a new model for multivariate time-series classification, called the hidden-unit logistic model (HULM), that uses binary stochastic hidden units to model latent structure in the ...

THOMASTON — Educators from across Georgia gathered at the GHSA offices Friday morning to discuss an objective that would seem difficult to oppose — arranging the association’s seven classifications to ...

Hi, We are working on Classification problem and it's research work. We are using YOLOV8x and we have four class and per each class around 2500 images. Accuracy that we achieved so far is ...

This valuable study considers empirical macroecological patterns in microbiome data across multiple taxonomic scales. The work convincingly shows that the Stochastic Logistic Growth model is a more ...