Care of terminally ill / Palliative care

Identification of Pathological Secretions in Bronchoscopic Images Based on Edge Features and Multi-Scale Attention Mechanism.

The accumulation of pathological bronchial secretions compromises ventilation and oxygenation in critically ill patients and may lead to atelectasis or secondary infection in severe cases, making timely identification and removal of pathological secretions essential during intensive care and surgical anesthesia. Conventional manual bronchoscopic assessment depends heavily on operator experience, l...

Bayesian convolutional front-end based uncertainty-aware hybrid quantum-classical image classification.

Quantum machine learning on noisy intermediate-scale quantum (NISQ) devices often suffers from noise sensitivity, small-data overfitting, and miscalibrated predictive confidence. We propose an uncertainty-aware hybrid Bayesian quantum neural network (BQNN) that couples a Bayesian convolutional front-end with a parameterized quantum circuit (PQC), forming a three-stage pipeline: Bayesian feature ex...

Democratizing Artificial Intelligence in Toxicology: Real-World Applications and Automated Computational Workflows.

Artificial intelligence (AI) and machine learning are transforming toxicological research and chemical safety assessment. Although user-friendly compu...

PipeBench: a benchmarking framework for end-to-end machine learning pipelines.

The integration of machine learning (ML) into modern data management systems has enabled intelligent decision-making across large-scale information in...

Artificial Intelligence-Supported Colorimetric Multibiomarker Sensor to Enable Critical Neonatal Monitoring.

Clinical monitoring in the most vulnerable patients, such as newborns, relies on invasive and costly procedures and/or wired sensor surveillance, incr...

Beyond Time Saved: Implementation, Equity, and the Utility Threshold for Nursing AI Scribes.

Schwabe et al's pre-post time-motion study of a domain-specific artificial intelligence (AI) speech assistant used by nurses in German long-term care ...

What do UK hospice websites communicate about the meaning of palliative care?

OBJECTIVES: Hospice websites are an important source of information for the public. This study examined whether information communicated about palliat...

End-to-end molecular structure elucidation from multimodal NMR spectra images using vision transformers.

Nuclear magnetic resonance (NMR) spectroscopy is a cornerstone technique for molecular structure elucidation, but interpreting complex NMR spectra rem...

Construction of a sports bio mechanical injury prediction and AI warning system based on wearable sensors.

BACKGROUND: Real-time warning and prevention of sports injuries are core challenges in the fields of sports medicine and health management. Traditiona...

Machine learning-driven high-throughput screening of electrocatalysts and electrolytes for electrochemical surfaces and interfaces.

Machine learning (ML) establishes a new paradigm for electrocatalyst and electrolyte research by coupling high-throughput screening (HTS) with a data-...

TVRN: Invertible Neural Networks for Compression-Aware Temporal Video Rescaling.

To fit diverse display and bandwidth constraints, high-frame-rate videos are temporally downscaled to low-frame-rate (LFR) and later upscaled, requiri...

Proactive soft-failure prediction in optical transport networks via physics-inspired features and Infrastructure-as-Code orchestration.

Optical transport networks rely on reactive fault management, which guarantees service disruption during the onset of soft failures. We present a fram...

Predicting fire consequences with the transformer model based on multimodal feature fusion.

Accurate prediction of fire consequences is fundamental to process safety management and quantitative risk assessment in the chemical process industri...

Biobanking in the Era of Artificial Intelligence: Convergence, Challenges, and Opportunities.

Artificial intelligence (AI) is advancing rapidly, transforming biomedical research and health care through software applications ranging from diagnos...

A hierarchical neuromorphic multi agent framework for energy aware and secure 6G resource optimization using Neuro6G agent.

The convergence of Sixth-Generation (6G) wireless networks and neuromorphic computing presents significant opportunities for intelligent, energy-effic...

Radiological staging clinical decision support model for rectal cancer lymph node metastasis detection on MRI.

BACKGROUND: Accurate staging of lymph node metastasis (LNM) is crucial for personalising rectal cancer treatment. Lymph nodes (LNs) are the most commo...

AI-Empowered and a Bio-/Nanoenzyme-Hybrid Multisensors Array toward Precision Diagnosis of Kidney Diseases.

Chronic kidney disease (CKD) risk assessment is shifting from centralized instrument-heavy testing to personalized point-of-care evaluation enabled by...

A Variational Mean-Field Control Framework for Graph Representation Learning.

Feature representation learning in graph neural networks (GNNs) is a dynamic process driven by progressive information exchange throughout the graph. ...

Machine Learning Prediction of Growth Hormone Response in Children Non-Growth Hormone-Deficient Short Stature.

Height gain under recombinant human growth hormone (rhGH) varies widely in children with short stature, making early, reliable response prediction ess...

Guideline-Aligned Machine Learning for Predicting Ondansetron Administration at the End of Anaesthesia: Explainable Decision Support for PONV Prophylaxis.

Artificial Intelligence (AI) and Clinical Practice Guidelines (CPGs) both aim to support clinical decision-making but may provide conflicting suggesti...