Optimizing RNA design with AI and an Ising machine: Encoding matters

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...
Eos

Comparing Machine Learning Models of Raindrop Formation

Better simulations of raindrop formation could help improve climate and weather models. This newsletter rocks. Get the most ...
IEEE

Hybrid Deep Machine Learning Feature Selection for High-Dimensional Cybersecurity Data

Abstract: The rapid increase in cyber threats has heightened the demand for Intrusion Detection Systems (IDS) that are both accurate and efficient. While deep learning models outperform traditional ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
Scientific American

Can AI help improve the chances of a successful IVF pregnancy?

Some IVF clinics are using AI to perform tasks such as sperm and embryo selection, but some fertility experts question ...
AZoM

Berkeley Lab Uses Advanced Machine Learning to Optimize Chiral Perovskites

Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the ...

MicroCloud Hologram Inc. Develops Approximate Quantum State Preparation and Entanglement-Dependent Complexity Algorithm Technology

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, has announced a groundbreaking achievement of great theoretical and engineering significance: its ...

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) (WIMI or the Company), a leading global Hologram Augmented Reality (AR) Technology ...
Frontiers

Mapping of groundwater protection zones using expert-driven and machine learning methods: a case study of Yulin City, China

Groundwater protection is critical for sustainable water resource management, particularly in arid regions. However, current zoning methods show challenges such as data bias of expert-driven models ...
Frontiers

Machine learning–guided feature selection and predictive model construction for attention-deficit/hyperactivity disorder

A total of 8,598 children were enrolled and classified into three groups: ADHD (n=3,678), subthreshold ADHD (s-ADHD) (n=1,495), and healthy controls (HC) (n=3,425). Data collection covered 40 ...
IEEE

Feature Selection for Battery Lifetime Prediction using Explainable Machine Learning

Abstract: Accurate battery lifetime estimation is crucial for health management and system safety. Data-driven research yields extensive feature sets, yet optimal feature selection is often impeded by ...