Infection control / Modes of transmission

Integrating Machine Learning with Musculoskeletal Simulation Improves OpenCap Video-Based Dynamics Estimation.

OBJECTIVE: Musculoskeletal dynamics influence the progression and rehabilitation of movement-related conditions. However, estimating whole-body dynamics using accessible tools, like smartphone video, remains challenging. Physics-based and machine learning (ML)-based dynamic predictions each offer advantages, but both approaches struggle to achieve high accuracy and physical realism. Here, we creat...

An ML-driven framework for continuous wearable health surveillance and energy-efficient communication.

Existing wireless body area network (WBAN) communication schemes often depend on fixed event assumptions, which results in redundant transmissions, poor energy utilization, and limited scalability in continuous health monitoring systems. To overcome these limitations, this paper introduces an machine learning-assisted (ML-assisted) Bitmap-Assisted MAC framework that employs data-driven transmissio...

In Situ Formation of Mechanical Interlocking Skin and Electronics Interfaces through Dual-Phase Transition of Conductive Materials.

The increasing demand for daily health monitoring has accelerated the development of wearable devices. However, conventional wearables, typically base...

A robust machine learning framework for predicting contact angle in nano-assisted chemical EOR.

Wettability alteration through nano-assisted chemical Enhanced Oil Recovery (nano-cEOR) critically governs capillary pressure and multiphase flow in p...

Towards structure-aware surrogate modeling: explicit region interaction improves knee contact stress prediction in young men.

Knee contact-stress hotspots are closely linked to meniscal/cartilage injury risk. Still, high-fidelity subject-specific FEA is too computationally ex...

Stochastic-Sampling-Based Event-Triggered Control for Switching Reaction-Diffusion Neural Networks.

This article addresses the issue of multiasynchronous time-space sampled-data control (SDC) for switching reaction-diffusion neural networks (SRDNNs) ...

A Central European tree species dataset of annotated terrestrial laser scanning point clouds - TreeScanPL10K.

Forest conservation and management are increasingly challenged by evolving societal expectations, biodiversity decline, and the impacts of climate cha...

Geometric deep learning enables high-fidelity network imputation for HIV transmission modeling.

BACKGROUND: Accurately mapping social and risk networks is critical for understanding and controlling infectious disease transmission, especially amon...

AI-based prediction of dengue incidence using climatic, environmental, and socio-demographic factors: an ensemble random forest approach with agile system development.

BACKGROUND: Dengue transmission in Indonesia is shaped by interacting climatic, environmental, and socio-demographic factors, yet most forecasting sys...

Artificial intelligence predictions of knee kinematics, kinetics, and internal biomechanics during walking in people with knee osteoarthritis: A systematic review and meta-analysis.

This review synthesizes current literature on the use of artificial intelligence (AI) to predict knee biomechanics during walking in people with knee ...

The architecture of computational antiviralism: a multi-scale framework from molecular targeting to viral ecosystem engineering.

The recurrent outbreak of viral pathogens and the possibility of the new pandemics demand the transition to the predictive and integrative computation...

Megahertz-rate down-sampled optical coherence tomography based on high-speed k-linear swept laser and deep learning.

Megahertz-rate optical coherence tomography (MHz-OCT) is an optical imaging technology that has attracted considerable attention in clinical practice....

Touch Modulates Gamma-Band Network Dynamics in the Infant Brain.

Touch is a foundational sensory modality in early development, playing a pivotal role in shaping social, emotional, and cognitive functions. This stud...

Temporal Trends and Projections of Leprosy in Brazil: Application of Machine Learning Techniques for Predictive Analysis (2001-2034).

Leprosy remains a neglected tropical disease with active transmission. Predictive models improve understanding of epidemiological trends and support c...

Machine Learning-Assisted Phase Diagram Determination in Aqueous Two-Phase Systems.

Accurate construction of phase diagrams for aqueous two-phase systems (ATPSs) is essential for identifying two-phase compositions for downstream appli...

FINS: An interactive platform for automated zebrafish image analysis and morphological screening.

MOTIVATION: Zebrafish embryo assays are increasingly recognized as a robust and scalable model for developmental toxicity screening due to embryos' op...

High-resolution mapping of onchocerciasis risk in Ghana using spatial machine learning models.

BACKGROUND: Onchocerciasis, caused by Onchocerca volvulus and transmitted through repeated bites of infected blackflies, remains endemic in several su...

Cost-effectiveness of infection prevention and control measures for carbapenem-resistant Gram-negative bacilli: A systematic review protocol.

INTRODUCTION: Multidrug-resistant organisms, including carbapenem-resistant Gram-negative bacilli (CRGNB), have a heavy health and economic burden in ...

Terabyte scale dataset for partial discharge detection in covered conductors via contact galvanic method.

This article introduces a dataset designed for the detection of partial discharges in transmission power lines using covered conductors through a cont...

Single-molecule localization and diffusivity microscopy reveals dynamic biomolecular organization in living cells.

Single-molecule tracking in living cells measures protein diffusivity but requires sparse imaging, limiting high-density mapping. Here we introduce si...