Care of terminally ill / Palliative care

Machine Learning-Enabled Intelligent Technologies Across the Grape and Wine Value Chain: From Vineyard Sensing to Winemaking Optimization.

Machine learning is transforming the grape and wine industry by shifting traditional experience-driven practices toward data-driven and intelligent decision making across the entire value chain. This review provides a conceptually driven synthesis of machine learning-enabled technologies spanning vineyard sensing, precision viticulture, fermentation monitoring, and winemaking optimization. An inte...

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-stage) estimation strategy where multiple independent operations (feature matching, two-view rotation estimation, and rotation averaging) are implemented sequentially. However, such a multi-stage strategy inevitably leads to the accumulation of the err...

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...

An agentic AI framework for integrated decision support and surgical planning in intracerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) remains associated with high mortality and treatment variability. Current workflows rely on fragmented imag...

Interpretable deep learning for rotator cuff calcific tendinopathy diagnosis: a multi-center study.

The reliable deployment of artificial intelligence systems in medical imaging requires high diagnostic performance, robustness and interpretability. I...

GreenAid: a confidence-weighted ensemble deep learning system for real-time plant disease detection and management.

Plant diseases cause 20-40% annual crop losses worldwide, yet conventional detection methods remain slow, subjective, and inaccessible to smallholder ...

Path beyond the blind end-unravel the imaging spectrum of appendiceal pathologies.

The appendix is involved in a diverse spectrum of inflammatory, infectious, benign, and malignant conditions that extend far beyond acute appendicitis...

VariantMedium: sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental data.

BACKGROUND: Accurately identifying somatic variants from genomic sequencing is crucial for understanding and treating cancer. Previously, methods base...

Full-spectrum EEM end-member unmixing with statistical validation: A deep learning framework for organic pollution source apportionment in complex watersheds.

Accurately apportioning organic pollution sources in mixed land-use watersheds remains challenging due to the limited tracer capacity of conventional ...

AutoRV: Automated Assessment of Right Ventricular Structure and Function Using Transesophageal Echocardiography in Mechanically Ventilated Patients.

OBJECTIVE: Right ventricle (RV) dysfunction has therapeutic implications for the management of mechanically ventilated patients in intensive care unit...

End-to-End PET/CT Interpretation and Quantification with an LLM-Orchestrated AI Agent: A Real-World Pilot Study.

Although deep learning models have improved individual PET analysis, image processing, and quantification tasks, end-to-end automation from raw DICOM ...