Care of terminally ill / Palliative care

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of elective aortobifemoral artery bypass for aortoiliac arterial occlusive disease based on variables at the time of preoperative clinical presentation utilizing 5,912 patients in the Vascular Quality Initiative (VQI). METHODS: Multivariable Cox regression time-dependent analysis was performed for the out...

Can health technologies be "care optimizers"? A normative evaluation of digital health technologies in light of postphenomenological reflections.

The integration of new technologies such as artificial intelligence (AI) into healthcare has initiated profound changes in clinical practice, reshaping not only clinical workflows but the relational structure of care itself. Among the most significant developments is the transformation of the traditional doctor–patient dyad into a doctor–patient–technology triad. Philosophical studies of technolog...

Leveraging generative AI to transform statistical analysis plan authoring in clinical trials.

BackgroundStatistical analysis plans are critical regulatory documents that define the statistical methodology, objectives, and data-handling procedur...

JAX Animal Behavior System (JABS), a genetics-informed, end-to-end advanced behavioral phenotyping platform for the laboratory mouse.

Automated detection of complex animal behavior remains a challenge in neuroscience. Developments in computer vision have greatly advanced automated be...

Impact of CT calibration curves on radiotherapy planning using diagnostic CT scans and a planning CT supporting DirectDensity reconstruction.

PURPOSE: DirectDensity enables tube voltage-independent, density-calibrated computed tomography (CT) images for treatment planning and is therefore in...

IoT framework for sports activity safety monitoring based on wearable sensors and CRNN spatiotemporal analysis.

The integration of wearable sensors and IoT technology provides new technical means for sports activity monitoring. However, existing solutions still ...

Resource constrained learning over wireless networks.

It is anticipated that the next generation of wireless networks will incorporate artificial intelligence (AI) to a significant degree at all network l...

LCMS-Net: Deep Learning for Raw High Resolution Mass Spectrometry Data Applied to Forensic Cause-of-Death Screening.

Current preprocessing workflows for untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) are time-consuming...

CapsFormer: A Dual-Stream Causal-Aware Capsule-Transformer Network for EMG Signal Representation Learning.

Electromyography (EMG) signals are widely applied in prosthetic control, rehabilitation training, and human-machine interaction. This places stringent...

Enhancing kelp origin prediction accuracy: A TabPFN model with stable isotope analysis and explainability techniques for robust insights.

Accurate prediction of kelp origin is essential for effective quality and safety management. To this end, we integrated the stable isotope ratios and ...

Physics-Informed Deep Learning for Shear Wave Speed Estimation in MR Elastography.

OBJECTIVE: Magnetic Resonance Elastography (MRE) is a non-invasive imaging technique for mapping biomechanical properties of in vivo tissue, including...

The Evaluation of Transformer Models for the Detection of Adverse Drug Events: A Benchmark Study Using Dutch Free-Text Documents of Hospitalized Patients.

INTRODUCTION: Adverse drug events (ADEs) are a leading cause of preventable patient harm in hospitals. Because they are often recorded only in clinica...

Real-Time Digital Micromotor Tracking-Enabled Ultrasensitive Immunoassay.

Digital bioassays are emerging as a pivotal technology in disease prevention and diagnostics due to their single-molecule level detection capability. ...

Modelling Follicular Growth During Ovarian Stimulation Using Agent-based Artificial Intelligence.

CONTEXT: Ovarian stimulation is a key step in medically assisted reproduction (MAR), whereby supraphysiological doses of FSH extend the "FSH window" a...

Deep learning-driven microfluidic chip architecture design for intelligent particle motion control.

Precise spatiotemporal manipulation of particles in complex microfluidic channel networks (MCNs) underlies numerous advanced applications, but remains...

DRfold2 is a deep learning-based tool that enables efficient and accurate RNA structure prediction.

RNA structures are essential for understanding their biological functions and developing RNA-targeted therapeutics. However, accurate RNA structure pr...

Investigating feature-engineered predictors for systolic blood pressure changes in an mHealth-based disease management program.

Mobile health (mHealth)-based disease management programs enable continuous monitoring of blood pressure (BP) and related health behaviors. Feature en...

An end-to-end convolutional neural network for secure image transmission via joint encryption and steganography.

Further attachment of image-based communication speed to sensitive areas must be provided with confidential and safe transmission. Conventional method...

An Adaptive Blockchain Framework for Federated IoMT with Reinforcement Learning-Based Consensus and Resource Forecasting.

The rapid growth of the Internet of Medical Things (IoMT) has increased the adoption of remote healthcare applications and telemedicine services. A Ma...

Multi-view graph clustering via dual attention fusion and collaborative optimization.

Multi-view graph clustering, a fundamental task in data mining and machine learning, aims to partition nodes into disjoint groups by leveraging comple...