Care of terminally ill / Palliative care

AI-Assisted Clinical Data Abstraction From Electronic Health Records: Retrospective Concordance Study.

BACKGROUND: Manual chart abstraction from electronic health records is a critical step in clinical outcomes research but is time-intensive and prone to human error. Advances in artificial intelligence (AI), particularly large language models, offer the potential to automate the extraction of structured data from unstructured clinical documentation with improved efficiency and consistency. OBJECTIV...

Early detection of severe fetal growth restriction using multimodal deep learning based on ultrasound and prenatal biomarkers.

OBJECTIVE: To develop and evaluate a multimodal deep learning model that integrates first- and second-trimester ultrasound images with first-trimester maternal serum biomarkers for early prediction of severe fetal growth restriction (FGR). MATERIALS AND METHODS: In this prospective study, 13,991 pregnant women were initially recruited, and after applying inclusion and exclusion criteria, 598 singl...

SqueakPose Studio, an end-to-end platform for pose estimation and real-time edge-AI deployment.

Accurate pose estimation underpins quantitative analysis of behavior, yet many deep learning-based tracking tools remain optimized for offline workflo...

Advancing low-carbon additive manufacturing: an integrated deep learning approach for optimal resource and capacity management.

As Additive Manufacturing (AM) shifts towards Make-to-Order (MTO) models, synchronizing raw material inventory with machine capacity becomes critical ...

End-to-end 2.5D multisequence-multichannel fusion model for preoperative survival prediction in glioma: a retrospective study.

Gliomas are the most common primary malignant tumors of the central nervous system and show marked imaging heterogeneity, making accurate preoperative...

Artificial intelligence-based prediction of transthoracic echocardiographic image quality in ICD/CRT-D candidates: A proof-of-concept study.

BACKGROUND: High-quality echocardiography is essential for accurate and reproducible assessment of cardiac functional indices, which are highly depend...

A blockchain-enabled IoT framework for smart electro-medical waste management.

Electro-medical waste (EMW) management presents critical challenges related to traceability, regulatory compliance, and operational safety in healthca...

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered...

End-to-End Autonomous Quantification of Brain Aneurysm and Parent Artery Morphology at CT Angiography.

Purpose To develop and validate an end-to-end autonomous platform for the quantification and visualization of brain aneurysm and parent artery morphol...

EAR-Net: Pursuing End-to-End Absolute Rotations from Multi-View Images.

Absolute rotation estimation is an important topic in 3D computer vision. Existing works in literature generally employ a multi-stage (at least two-st...

Operationalizing Digital Health Equity in Artificial Intelligence-Enabled Patient Decision Aids for Older Adults: Mixed Methods Study.

BACKGROUND: Artificial intelligence-enabled patient decision aids (AI-PDAs) hold promise for supporting older adults with chronic diseases in accessin...

Dynamic low-altitude airspace partitioning and management strategy optimization based on graph neural networks and spatial cognitive constraints.

The rapid expansion of urban air mobility operations demands adaptive airspace management approaches that transcend traditional static sectorization. ...

DAPR-AM-Net: an end-to-end smart farming system powered by dual-attention progressive refinement and adaptive MixUp for explainable tomato leaf disease classification and forecasting.

Vision-based crop disease diagnosis plays a pivotal role in smart agriculture, yet challenges such as complex field backgrounds, high intra-class simi...

Topology-decoupled end-to-end framework for brain tumor MRI detection: boundary-preserving feature flow and inter-channel correlation distillation.

Early and accurate detection of brain tumors is clinically valuable for improving prognosis and guiding treatment. Existing deep-learning methods for ...

Uncertainty-aware deep kernel learning: An end-to-end approach for crack localization in turbine blades.

Early and reliable crack localization in jet turbine blades is important for structural health monitoring in aerospace systems. This study presents an...

Enhancing enterprise decision support via swin transformer-based OCR-free information extraction.

Extracting key information from vast amounts of documents and data plays a crucial role in knowledge graph construction, intelligence analysis, decisi...

Right Ventricular Metrics as End Points in Clinical Trials: A Review.

IMPORTANCE: Clinical trials in cardiovascular medicine aim to deliver high-quality evidence with greater efficiency, including smaller sample sizes an...

Discrete Wavelet Convolution for Learnable Time-Frequency Representation with Application to Seizure Prediction.

Accurate and adaptive time-frequency representation is essential for analyzing nonstationary signals in critical applications, such as epileptic seizu...

Automation in the IVF laboratory in 2026: four technology domains, an asymmetric evidence base, and the case for parallel development with clinician-side automation.

BACKGROUND: Operator-dependent laboratory tasks-embryo selection, vitrification and warming, and intracytoplasmic sperm injection (ICSI)-have been the...

EdgeVolution: democratizing multi-objective neural architecture search and end-to-end deployment on microcontrollers.

Edge AI holds great potential for extending the use of artificial neural networks to resource-constrained edge devices, such as microcontrollers. Desp...