Hospital AI tool predicts low blood sugar in patients up to 24 hours in advance

Cedars-Sinai Health Sciences University investigators developed an AI-based model that can identify hospitalized patients at ...
IEEE

Geo-LSTM: A Geometry and Temporal Feature Fusion Algorithm for Multi-Sensor 3D Localization

Abstract: Accurate three-dimensional (3D) localization is critical for robust human-robot collaboration (HRC) in dynamic indoor environments. However, realizing high-precision localization in complex ...
IEEE

A Novel Hybrid GCN-LSTM Algorithm for Energy Stock Price Prediction: Leveraging Temporal Dynamics and Inter-Stock Relationships

Abstract: Energy stock price prediction is a pivotal challenge in financial forecasting, characterized by high volatility and complexity influenced by geopolitical factors, regulatory shifts, and ...
EurekAlert!

LSTM resolves the long-standing trade-off between sensitivity and measurement range

Light Publishing Center, Changchun Institute of Optics, Fine Mechanics And Physics, CAS For a long time, optical interferometric sensors have been widely used in rapid and real-time detection in ...
Frontiers

Intelligent maneuver decision-making for UAVs using the TD3–LSTM reinforcement learning algorithm under uncertain information

Aiming to address the complexity and uncertainty of unmanned aerial vehicle (UAV) aerial confrontation, a twin delayed deep deterministic policy gradient (TD3)–long short-term memory (LSTM) ...
Frontiers

Cable laying conveyor state prediction and fault warning based on attention-driven CNN-LSTM algorithm

The monitoring condition of the cable laying conveyor, such as rotational speed, driving current, and side pressure, reflects the real-time operation status of the cable laying process. Accurate ...
Scientific Research Publishing

Logistics Demand Forecast of Fresh Food E-Commerce Based on Bi-LSTM Model ()

Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper ...