Critical Care

Score-based Self-supervised MRI Denoising

Magnetic resonance imaging (MRI) is a powerful noninvasive diagnostic imaging tool that provides unparalleled soft tissue contrast and anatomical detail. Noise contamination, especially in accelerated and/or low-field acquisitions, can significantly degrade image quality and diagnostic accuracy. Supervised learning based denoising approaches have achieved impressive performance but require high ...

MDE-Edit: Masked Dual-Editing for Multi-Object Image Editing via Diffusion Models

Multi-object editing aims to modify multiple objects or regions in complex scenes while preserving structural coherence. This task faces significant challenges in scenarios involving overlapping or interacting objects: (1) Inaccurate localization of target objects due to attention misalignment, leading to incomplete or misplaced edits; (2) Attribute-object mismatch, where color or texture change...

MoRe-3DGSMR: Motion-resolved reconstruction framework for free-breathing pulmonary MRI based on 3D Gaussian representation

This study presents an unsupervised, motion-resolved reconstruction framework for high-resolution, free-breathing pulmonary magnetic resonance imagi...

Image Restoration via Multi-domain Learning

Due to adverse atmospheric and imaging conditions, natural images suffer from various degradation phenomena. Consequently, image restoration has eme...

A Dataset and Toolkit for Multiparameter Cardiovascular Physiology Sensing on Rings

Smart rings offer a convenient way to continuously and unobtrusively monitor cardiovascular physiological signals. However, a gap remains between th...

Tri-MTL: A Triple Multitask Learning Approach for Respiratory Disease Diagnosis

Auscultation remains a cornerstone of clinical practice, essential for both initial evaluation and continuous monitoring. Clinicians listen to the l...

Prototype-Based Information Compensation Network for Multi-Source Remote Sensing Data Classification

Multi-source remote sensing data joint classification aims to provide accuracy and reliability of land cover classification by leveraging the comple...

Event-Triggered GAT-LSTM Framework for Attack Detection in Heating, Ventilation, and Air Conditioning Systems

Heating, Ventilation, and Air Conditioning (HVAC) systems are essential for maintaining indoor environmental quality, but their interconnected natur...

ChatGPT for automated grading of short answer questions in mechanical ventilation

Standardised tests using short answer questions (SAQs) are common in postgraduate education. Large language models (LLMs) simulate conversational la...

MUSAR: Exploring Multi-Subject Customization from Single-Subject Dataset via Attention Routing

Current multi-subject customization approaches encounter two critical challenges: the difficulty in acquiring diverse multi-subject training data, a...

Enhancing LLMs' Clinical Reasoning with Real-World Data from a Nationwide Sepsis Registry

Although large language models (LLMs) have demonstrated impressive reasoning capabilities across general domains, their effectiveness in real-world ...

From Biometrics to Environmental Control: AI-Enhanced Digital Twins for Personalized Health Interventions in Healing Landscapes

The dynamic nature of human health and comfort calls for adaptive systems that respond to individual physiological needs in real time. This paper pr...

Multi-Scale Graph Learning for Anti-Sparse Downscaling

Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature ...

Early Detection and Remote Care of Frailty for Older Adults Living in Sparsely Populated Rural Areas in Hokkaido, Japan: A Case Study.

The global increase in the number of older people aged 65 and over is causing concern in healthcare and social systems. The lack of health and welfare...

Probability Score for the Diagnosis of Periprosthetic Joint Infection: Development and Validation of a Practical Multi-analyte Machine Learning Model.

Background and objective The diagnosis of periprosthetic joint infection (PJI) relies on established criteria-based systems requiring interpretation a...

Preparing for Vascular Surgery Board Certification: A Comparative Study Using Large Language Models.

Introduction and aim Large language models (LLMs) are transforming medical education by offering innovative methods to enhance teaching and learning. ...

Generative AI mitigates representation bias and improves model fairness through synthetic health data.

Representation bias in health data can lead to unfair decisions and compromise the generalisability of research findings. As a consequence, underrepre...

Predicting Respiratory Disease Mortality Risk Using Open-Source AI on Chest Radiographs in an Asian Health Screening Population.

Purpose To assess the prognostic value of an open-source deep learning-based chest radiographs algorithm, CXR-Lung-Risk, for stratifying respiratory d...

Association of Deep Learning-based Chest CT-derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis.

Background Forced vital capacity (FVC) is a standard measure of respiratory function in patients with amyotrophic lateral sclerosis (ALS) but has limi...

A hybrid approach for binary and multi-class classification of voice disorders using a pre-trained model and ensemble classifiers.

Recent advances in artificial intelligence-based audio and speech processing have increasingly focused on the binary and multi-class classification of...