Real-Time Traffic Speed Estimation With Graph Convolutional Generative Autoencoder Abstract: Real-time traffic speed estimation is an essential component of intelligent transportation system (ITS) ...

This paper studies the computational offloading of CNN inference in dynamic multi-access edge computing (MEC) networks. To address the uncertainties in communication time and edge servers’ available ...

Variants of obesity-related genes influence how much weight patients lose on specific weight loss drugs like liraglutide, two studies report.

BACKGROUND: A role for leptin to predict weight gain is still controversial. OBJECTIVE AND DESIGN: To determine the relationship between baseline serum leptin values and responsiveness to an ...

However, although the use of machine learning algorithms to predict low birth weight is gaining ground globally, most studies have been conducted in high-income countries.

High BMI, nutritionist support, and liver stiffness measures may predict relevant weight loss in patients with metabolic dysfunction‐associated steatotic liver disease.

Viking Therapeutics stock remains under pressure, but analysts said Wednesday the company's strategy for its Phase 3 studies could pay off.

How did the tiler predict？ How is the preprocessing done? Does it involve division by 255?

I'm trying to create my own minimal inference engine without direct dependency of XGBoost itself. My final goal is to implement it in Rust but here I first test the concept in Python. I started from ...

Motorola Edge (2024) Android smartphone. Announced Jun 2024. Features 6.6″ display, Snapdragon 7s Gen 2 chipset, 5000 mAh battery, 256 GB storage, 8 GB RAM, Corning Gorilla Glass 3.