Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 441 to 450 of 158,332 articles

Real-Time jamming detection using windowing and hybrid machine learning models for pre-saturation alerts.

Scientific reports
This paper proposes a new deep learning and machine learning model for detecting deception and suppression jamming in Ublox-M8T receivers operating under GNSS interference. This solution employs XGBoost for real-time classification of jamming signals...

Integrating deep learning in stride-to-stride muscle activity estimation of young and old adults with wearable inertial measurement units.

Scientific reports
Deep learning has become powerful and yet versatile tool that allows for the extraction of complex patterns from rich datasets. One field that can benefits from this advancement is human gait analysis. Conventional gait analysis requires a specialize...

PZT optical memristors.

Nature communications
Optical memristors represent a monumental leap in the fusion of photonics and electronics for neuromorphic computing and artificial intelligence. Here, we reveal the first lead zirconate titanate (PZT) optical memristor, working with a paradigm of fu...

Deep ensemble learning with transformer models for enhanced Alzheimer's disease detection.

Scientific reports
The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties over time. Currently, there is no remedy for this illness. Accurate detection and prompt intervention are pivotal in mitigating the progression of the di...

Hybrid deep learning framework for real-time DO prediction in aquaculture.

Scientific reports
Dissolved oxygen (DO) is a vital parameter in regulating water quality and sustaining the health of aquatic organisms in aquaculture environments. Therefore, estimation and control of DO levels are essential in aquaculture operations. However, tradit...

Making data markets: Assetization, valuation, and proxy work in a digital health start-up.

Social studies of science
Digital data are increasingly framed as essential resources in health and medicine, implicating diverse actors who work to transform them into different forms of value. In this article we focus on the diverse and contingent valuation practices that s...

Exploring graph-based models for predicting active compounds against triple-negative breast cancer.

Molecular diversity
Breast cancer is among the most dominant and rapidly rising cancers, both in India and around the world. Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer, distinguished by the absence of HER2, progesterone,...

Hyperbolic multi-channel hypergraph convolutional neural network based on multilayer hypergraph.

Scientific reports
In recent years, hypergraph neural networks have achieved remarkable success in tasks such as node classification, link prediction, and graph classification, thanks to their powerful computational capabilities. However, most existing hypergraph neura...

Can Neural Networks Learn Atomic Stick-Slip Friction?

ACS applied materials & interfaces
Nanofriction experiments typically produce force traces exhibiting atomic stick-slip oscillations, which researchers have traditionally analyzed with ad hoc algorithms. This study successfully unravels the potential of machine learning (ML) to interp...

Overcoming Information Sparsity in Metasurfaces for Full-Color Holography via End-to-End Design.

Nano letters
We propose an end-to-end (E2E) system for RGB meta-hologram generation that efficiently determines the optimal material and geometry for target holograms, eliminating the need for exhaustive simulations of every possible meta-atom configuration. A ne...