Care of terminally ill / Palliative care

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. In this study, we developed and evaluated two automated frameworks for binary classification of shoulder radiographs (XRs) using deep learning (DL) and hybrid DL-machine learning (ML) approaches. A convolutional neural network (CNN) based on a fine-tu...

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 farmers. This work presents GreenAid, an end-to-end plant disease detection and management system that bridges the gap between laboratory-level deep learning performance and practical agricultural deployment. The system integrates a confidence-weight...

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 ...

Design and simulation of a hybrid PLC-AI automotive control module for adaptive lighting and honking.

Excessive honking and improper use of the headlamp beam significantly impact driving safety at night through visual impairment caused by headlamp beam...

Development of an Arterial Carbon Dioxide Estimation Model Using End-Tidal Carbon Dioxide Levels during Surgery in the Pediatric Population.

BACKGROUND: Intraoperative arterial carbon dioxide partial pressure monitoring is essential for pediatric ventilatory management but requires invasive...

Robust adaptive fault-tolerant learning control for human height-weight prediction based on DNN.

In this paper, a distributed robust adaptive confined fault-tolerant optimal control method based on deep neural networks is proposed, aiming to solve...

Implementing Digital Respiratory Technologies for People With Respiratory Conditions: Scoping Review.

BACKGROUND: Digital health offers opportunities for safe, equitable, and accessible care, and its integration into respiratory care is a strategic pri...

A Physics-Guided Neural Network Framework for Prediction and Control of Spring-Mass Running.

The spring-mass template acts as a fundamental bridge between animal locomotion and legged robotic platforms. However, controlling spring-mass dynamic...

Adversarial sample generation technology combining benign salient areas and improved GAN in white-box and black-box attack scenarios.

A end-to-end malware visual security assessment and defense framework is proposed to address the serious vulnerability faced by malware visual classif...

End-to-end robust system discovery in electrical dynamical systems using scientific machine learning.

System discovery is an important part of the power systems asset management process. In this paper, we introduce an end-to-end approach for robust sys...

Large language models integrated into brain-computer interfaces for communication and control: a systematic review.

Large language models (LLMs) are starting to be coupled with brain-computer interfaces (BCIs) for assistive communication, but the resulting systems d...

E2E-OCT: end-to-end joint learning model using optical coherence tomography images for vocal cord leukoplakia diagnosis.

In our previous study, a home-built handheld OCT system was used to collect OCT images in vocal cord leukoplakia. First, 383 valid OCT images were col...

Hybrid control scheme of nonlinear model prediction and adaptive terminal sliding mode for underwater vehicles based on threshold switching.

This paper addresses the challenge of balancing real-time performance and control smoothness in trajectory tracking for underwater vehicles. To this e...

MutAIverse: an AI-powered, mechanism-backed platform for discovering novel DNA adducts and their precursor genotoxins.

Genotoxin exposure leads to DNA adduct formation, potentially causing mutations if unrepaired. Current DNA adductomics platforms or analytical workflo...

An AI-Driven H5P Training for Epilepsy Emergency Management Preparedness in Dental Education.

BACKGROUND: Deficiencies in knowledge and skills related to the management of medical emergencies in dental settings can adversely affect the clinical...

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery.

Large language models can synthesize biomedical knowledge, parse vast amounts of data, and generate code, positioning them as promising tools for biom...