Care of terminally ill / Palliative care

Hybrid CNN-decision tree framework for efficient transmission line fault detection and classification: an XAI-based approach.

Accurate, fast, and interpretable fault identification on electrical transmission lines is essential for maintaining power system stability and reducing outage durations. In this study, we propose a hybrid 1D convolutional neural network-Decision Tree (1D-CNN-DT) for transmission line fault detection and classification, in which the 1D-CNN acts solely as a feature extractor. During this process, t...

Time Savings Through an AI Speech Assistant for Nursing Documentation: Pre-Post Time-Motion Study in German Long-Term Care.

BACKGROUND: Nurses in long-term care spend up to one-third of their working time on documentation, contributing to administrative burden and limited time for direct care. Artificial intelligence (AI) speech assistants have shown potential to accelerate documentation, but longitudinal evidence from real-world long-term care settings remains scarce. OBJECTIVE: This study aimed to evaluate whether im...

A double-blind, crossover, non-inferiority randomised controlled trial where primary care providers and patients compare human-generated and AI-generated digital health messages: the AI-CARE study protocol.

INTRODUCTION: Primary care is facing multiple crises, including an increase in health misinformation. Digital health messaging by primary care provide...

Inverse design of an ultra-wideband endfire grooved half-mode waveguide (G-HMWG) antenna based on the CNN approach.

This study presents an AI-assisted inverse design methodology for a compact and ultra-wideband grooved half-mode waveguide (G-HMWG) end-fire antenna. ...

Determinants of LV Myocardial Dyssynchrony in CHF: Impact of Mechanical and Electrical Dyssynchrony.

Chronic heart failure (CHF) patients often present with heterogeneous patterns of cardiac dyssynchrony. Although QRS prolongation (>150 ms) and left b...

Targeted Real-Time Assessment of Chronic Pain (TRAC-Pain) in Youth: Protocol for a Digital Biosignature Development Through a Prospective Observational Cohort Study.

BACKGROUND: Approximately 1 in 5 children and adolescents live with chronic pain, with musculoskeletal (MSK) pain being one of the most prevalent subt...

An effluent risk informed closed-loop framework for early warning of influent anomalies using COD soft sensing.

Sudden shock loads in wastewater influent can severely disrupt biological treatment processes and cause effluent quality exceedances in wastewater tre...

Emotion-driven front-end design of NEVs using an improved LSTM with LDA-based emotion mining.

Due to the inherent subjectivity of Kansei perception, aligning the front-end styling of new energy vehicles (NEVs) with users' emotional preferences ...

An Ensemble of Long Short-Term Memory Models to Automatically Detect End-Range Movement Patterns in Men's Professional Hard Court Grand Slam Tennis.

Evaluating end-range movements during tennis match-play can quantify high intensity load exposure and facilitate specific analysis of players' high-en...

DIGITAL SOLUTIONS FOR TUBERCULOSIS SURVEILLANCE AND CONTROL IN PRIMARY HEALTH CARE: A SCOPING REVIEW.

Digital solutions are essential for eliminating tuberculosis as a public health problem. They can be applied across all stages of patient care, health...

MAN++: Scaling Momentum Auxiliary Network for Supervised Local Learning in Vision Tasks.

End-to-end backpropagation remains the dominant training paradigm in deep learning, yet it suffers from inherent drawbacks, including update locking, ...

Toward Robust End-to-End Delay Prediction: A GNN Approach With Routing-Aware Attention and Masked Subgraph Sampling.

The end-to-end delay prediction is critical for intelligent network management, particularly in latency-sensitive and dynamic environments. While rece...

TSMPI-Net: a time-series generative adversarial network for short-frame-interval magnetic particle imaging.

OBJECTIVE: Magnetic particle imaging (MPI) is an emerging imaging modality that offers high sensitivity and potential for high-speed imaging. In many ...

AI-generated Feedback Following Social Robotic Virtual Patient Interactions and Medical Student Performance: Nonrandomized Quasi-Experimental Study.

BACKGROUND: Virtual patients (VPs) demonstrate effectiveness in improving clinical reasoning skills; however, traditional VP platforms often lack indi...

A Bilingual Arabic-English Ambient AI Scribe for Clinical Documentation: Prospective Evaluation Study.

BACKGROUND: Medical ambient artificial intelligence (AI) scribes reduce documentation burden, but the current evidence is almost entirely from English...

Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol for an Observational Study.

BACKGROUND: The promise of artificial intelligence (AI) in medicine depends on its ability to learn from data that reflect what matters to patients an...

Deep-Learning-Based Image Reconstruction to Improve End-Diastolic and Systolic Cardiac T1 Mapping.

PURPOSE: To develop an image reconstruction method that enables increased spatial resolution cardiac T1 mapping in both the end-diastolic and systolic...

PestDetectSim: an integrated approach for crop pest diagnosis using object detection and similarity-based image retrieval.

BACKGROUND: Rapid and accurate pest diagnosis is essential for reducing crop losses and improving agricultural productivity. Most existing methods rel...

Towards real-time sleep stage classification: A deep learning approach leveraging PPG and ECG.

OBJECTIVE: This work aims to enable adaptive Consumer Sleep Technologies (CSTs) for sleep intervention by developing a deep learning model for sleep s...

Prognostic value of end-to-end deep learning assessment of myocardial scar and microvascular obstruction on late gadolinium enhancement cardiovascular magnetic resonance.

BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the reference standard for assessing myocardial scar and micr...