Care of terminally ill / Palliative care

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 injury and evolving instability. However, risk prediction in later phases-after revascularization-is less explored, despite its importance in guiding intensive care decisions. This study evaluates machine learning (ML) models for dynamic risk assessment ...

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 architectures capable of supporting intelligent analytics and predictive maintenance. This paper presents a novel comprehensive architecture that enables end-to-end processing of IoT data streams, from acquisition to actionable insights. The system in...

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...

Model interpretability on private-safe oriented student dropout prediction.

Student dropout is a significant social issue with extensive implications for individuals and society, including reduced employability and economic do...

Electric vehicle braking energy recovery control method integrating fuzzy control and improved firefly algorithm.

Braking energy recovery is crucial for improving the energy efficiency and extending the range of electric vehicles. If a large amount of braking ener...

Leveraging Extended Windows in End-to-End Deep Learning for Improved Continuous Myoelectric Locomotion Prediction.

Current surface electromyography (sEMG) methods for locomotion mode prediction face limitations in anticipatory capability due to computation delays a...

PULSE: A DL-Assisted Physics-Based Approach to the Inverse Problem of Electrocardiography.

This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) metho...

Deep Learning for High Speed Optical Coherence Elastography With a Fiber Scanning Endoscope.

Tissue stiffness is related to soft tissue pathologies and can be assessed through palpation or via clinical imaging systems, e.g., ultrasound or magn...

Multitask Deep Learning Models of Combined Industrial Absorption, Distribution, Metabolism, and Excretion Datasets to Improve Generalization.

The optimization of absorption, distribution, metabolism, and excretion (ADME) profiles of compounds is critical to the drug discovery process. As suc...

BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, ...

Learning Consistent Semantic Representation for Chest X-ray via Anatomical Localization in Self-Supervised Pre-Training.

Despite the similar global structures in Chest X-ray (CXR) images, the same anatomy exhibits varying appearances across images, including differences ...

Enhancing diagnosis prediction with adaptive disease representation learning.

Diagnosis prediction predicts which diseases a patient is most likely to suffer from in the future based on their historical electronic health records...

Transforming residential water end use analysis: unleashing insights from widespread low-resolution smart metering data.

Transforming smart meter data captured at low-resolution litre intervals of 15 to 60 mins into residential water end use data provides valuable insigh...

Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem.

The purpose of this article is to evaluate the application of artificial intelligence (AI) from the perspective of the orthopaedic industry with respe...