Care of terminally ill / Palliative care

Computer-Vision Approach to Triaging Patient-Submitted Photos of Intestinal Ostomies.

BACKGROUND: Surgeons and ostomy nurses receive a high volume of stoma photos from patients. OBJECTIVE: This study aimed to develop and validate an automated and scalable artificial intelligence pipeline for identification and triage of patient-submitted intestinal ostomy photos. DESIGN: Retrospective derivation and validation study with stakeholder engagement to guide model design. Clinical teams ...

Machine Learning-Guided Near-Infrared Laser Processing for Precise Geometry Control in Microneedles with Downstream microLED-Triggered Photothermal Functionality.

Transdermal drug delivery and sensing provide non-invasive routes for localized therapy and biomarker detection. Microneedles (MNs) enable pain-free access to subdermal layers; however, variations in skin thickness and stiffness across anatomical sites demand precise control over MN geometry. This study presents a machine learning-guided approach for predictive fabrication of MNs using near-infrar...

End-to-end deep learning for flight trajectory reconstruction from multi-station ADS-B measurements.

In the field of aviation safety, ADS-B is widely adopted as an active broadcast-based aviation surveillance system, enabling aircraft to broadcast the...

Patient- and Caregiver-Informed Considerations for the Design and Implementation of Generative AI-Supported Patient-Centered Clinical Decision Support: Qualitative Study.

BACKGROUND: Generative artificial intelligence (AI) has the potential to impact health care by transforming workflows and improving outcomes. Patient-...

A unified multi-modal foundation model for end-to-end emergency care.

Against the backdrop of population aging and the rising burden of chronic diseases in China, emergency departments (EDs) in tertiary hospitals remain ...

Personalized learning path recommendation for middle school students based on joint optimization of deep reinforcement learning and knowledge tracing.

The rapid advancement of personalized education has created an urgent need for intelligent learning path recommendation systems that can dynamically a...

Mind the gap: An embedding guide to safely travel in sequence space.

We present a hybrid approach combining a protein language model (pLM) with Monte Carlo (MC) sampling for generating enzyme mutants free of mutations d...

TimeSight: Kinetics-aware detection for digital nucleic acid amplification via spatiotemporal convolutional learning.

Digital nucleic acid amplification enables absolute molecular quantification by partitioning samples into thousands of micro-reactions, yet current an...

AI-Based Segmental Volumetry of the Downstream Aorta in Aortic Dissection: End-to-End Versus Hybrid Strategies.

Automated segmental volumetry is effective for aortic dissection surveillance but lacks standardization. This study aimed to identify the optimal deep...

A predictive model for early neurological deterioration in medullary infarction based on explainable machine learning.

BACKGROUND: Medullary infarction is a severe subtype of ischemic stroke. Early neurological deterioration (END) is a common adverse event that can sig...

LeafLiteX mobile application for leaf disease detection using U-Net segmentation and lightweight deep learning.

Agriculture is significant in world food production and global economic stability, but leaf disease and pest infection can cause a threat to crop quan...

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 t...

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...

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...