Care of terminally ill / Palliative care

Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction.

Accurate traffic flow prediction is vital for intelligent transportation systems but presents significant challenges. Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to...

A Machine Learning Model to Predict Treatment Effect Associated with Targeted Temperature Management After Cardiac Arrest.

BACKGROUND: Targeted temperature management (TTM) has been associated with neurological recovery among comatose survivors of cardiac arrest. The aim of this study is to determine whether models leveraging acute phase multimodal data after intensive care unit admission (hyperacute phase) can predict short-term outcome after TTM. METHODS: Clinical, physiologic, and laboratory data in the hyperacute ...

End-to-end 2D/3D registration from pre-operative MRI to intra-operative fluoroscopy for orthopedic procedures.

PURPOSE: Soft tissue pathologies and bone defects are not easily visible in intra-operative fluoroscopic images; therefore, we develop an end-to-end M...

HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images.

Accurate measurement of hallux valgus angle (HVA) and intermetatarsal angle (IMA) is essential for diagnosing hallux valgus and determining appropriat...

DeepMS: super-fast peptide identification using end-to-end deep learning method.

Mass spectrometry (MS) has emerged as a powerful omics analysis technique, particularly in proteomics, where the initial step involves identifying MS ...

ToPoMesh: accurate 3D surface reconstruction from CT volumetric data via topology modification.

Traditional computed tomography (CT) methods for 3D reconstruction face resolution limitations and require time-consuming post-processing workflows. W...

Applications of artificial intelligence in abdominal imaging.

The rapid advancements in artificial intelligence (AI) carry the promise to reshape abdominal imaging by offering transformative solutions to challeng...

Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells.

Deep learning-based methods for identifying and tracking cells within microscopy images have revolutionized the speed and throughput of data analysis....

Learning double balancing representation for heterogeneous dose-response curve estimation.

Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and manag...

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices.

The proliferation of end devices has led to a distributed computing paradigm, wherein on-device machine learning models continuously process diverse d...

Screen shooting resistant watermarking based on cross attention.

With the development of digital imaging devices, the process of recording sensitive information displayed on screens through mobile phones and cameras...

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persists after revascularization due to reperfusion inju...

End-to-End Architecture for Real-Time IoT Analytics and Predictive Maintenance Using Stream Processing and ML Pipelines.

The rapid proliferation of Internet of Things (IoT) devices across industries has created a need for robust, scalable, and real-time data processing a...

Event driven neural network on a mixed signal neuromorphic processor for EEG based epileptic seizure detection.

Long-term monitoring of biomedical signals is essential for the modern clinical management of neurological conditions such as epilepsy. However, devel...

A controller of robot constant force grinding based on proximal policy optimization algorithm.

In order to solve the problems of high dependence on the accuracy of environmental model and poor environmental adaptability of traditional control me...

An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans.

Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These...

Artificial Intelligence: Applications in Pharmacovigilance Signal Management.

Pharmacovigilance is the science of collection, detection, and assessment of adverse events associated with pharmaceutical products for the ongoing mo...

Tracking control of robotic manipulator end-effector trajectory based on robust sliding mode method.

This paper addresses the precise trajectory tracking of robotic manipulators (RMs) in automation tasks, particularly in hazardous environments. A dyna...

A Novel Hierarchical Cross-Stream Aggregation Neural Network for Semantic Segmentation of 3-D Dental Surface Models.

Accurate teeth delineation on 3-D dental models is essential for individualized orthodontic treatment planning. Pioneering works like PointNet suggest...

TransformDDI: The Transformer-Based Joint Multi-Task Model for End-to-End Drug-Drug Interaction Extraction.

Drug-Drug Interactions (DDI) identification is a part of the drug safety process, that focuses at avoiding potential adverse drug effects that can lea...