Critical Care

MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification

Medical time series has been playing a vital role in real-world healthcare systems as valuable information in monitoring health conditions of patients. Accurate classification for medical time series, e.g., Electrocardiography (ECG) signals, can help for early detection and diagnosis. Traditional methods towards medical time series classification rely on handcrafted feature extraction and statis...

AI-Based Thermal Video Analysis in Privacy-Preserving Healthcare: A Case Study on Detecting Time of Birth

Approximately 10% of newborns need some assistance to start breathing and 5\% proper ventilation. It is crucial that interventions are initiated as soon as possible after birth. Accurate documentation of Time of Birth (ToB) is thereby essential for documenting and improving newborn resuscitation performance. However, current clinical practices rely on manual recording of ToB, typically with minu...

Multi-illuminant Color Constancy via Multi-scale Illuminant Estimation and Fusion

Multi-illuminant color constancy methods aim to eliminate local color casts within an image through pixel-wise illuminant estimation. Existing metho...

Multi-Resolution SAR and Optical Remote Sensing Image Registration Methods: A Review, Datasets, and Future Perspectives

Synthetic Aperture Radar (SAR) and optical image registration is essential for remote sensing data fusion, with applications in military reconnaissa...

CycleGuardian: A Framework for Automatic RespiratorySound classification Based on Improved Deep clustering and Contrastive Learning

Auscultation plays a pivotal role in early respiratory and pulmonary disease diagnosis. Despite the emergence of deep learning-based methods for aut...

Sampling Binary Data by Denoising through Score Functions

Gaussian smoothing combined with a probabilistic framework for denoising via the empirical Bayes formalism, i.e., the Tweedie-Miyasawa formula (TMF)...

Artificial Intelligence-Based Early Prediction of Acute Respiratory Failure in the Emergency Department Using Biosignal and Clinical Data.

PURPOSE: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing bi...

Speech Detection via Respiratory Inductance Plethysmography, Thoracic Impedance, Accelerometers, and Gyroscopes: A Machine Learning-Informed Comparative Study.

Speech production interferes with the measurement of changes in cardiac vagal activity during acute stress by attenuating the expected drop in heart r...

BSODiag: A Global Diagnosis Framework for Batch Servers Outage in Large-scale Cloud Infrastructure Systems

Cloud infrastructure is the collective term for all physical devices within cloud systems. Failures within the cloud infrastructure system can sever...

Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior

Recent advancements in diffusion models have been leveraged to address inverse problems without additional training, and Diffusion Posterior Samplin...

Identification of DNA damage repair-related genes in sepsis using bioinformatics and machine learning: An observational study.

Sepsis is a life-threatening disease with a high mortality rate, for which the pathogenetic mechanism still unclear. DNA damage repair (DDR) is essent...

Vagus nerve stimulation as a modulator of feedforward and feedback neural transmission

Vagus nerve stimulation (VNS) has emerged as a promising therapeutic intervention across various neurological and psychiatric conditions, including ...

Snapshot multi-spectral imaging through defocusing and a Fourier imager network

Multi-spectral imaging, which simultaneously captures the spatial and spectral information of a scene, is widely used across diverse fields, includi...

Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays

Chest X-rays play a pivotal role in diagnosing respiratory diseases such as pneumonia, tuberculosis, and COVID-19, which are prevalent and present u...

The Lock Generative Adversarial Network for Medical Waveform Anomaly Detection

Waveform signal analysis is a complex and important task in medical care. For example, mechanical ventilators are critical life-support machines, bu...

Contrastive Representation Learning Helps Cross-institutional Knowledge Transfer: A Study in Pediatric Ventilation Management

Clinical machine learning deployment across institutions faces significant challenges when patient populations and clinical practices differ substan...

InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model

Despite the promising performance of Large Vision Language Models (LVLMs) in visual understanding, they occasionally generate incorrect outputs. Whi...

Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution

With the rapid advancement of Multi-modal Large Language Models (MLLMs), MLLM-based Image Quality Assessment (IQA) methods have shown promising perf...

Deformable Image Registration of Dark-Field Chest Radiographs for Local Lung Signal Change Assessment

Dark-field radiography of the human chest has been demonstrated to have promising potential for the analysis of the lung microstructure and the diag...

Semi-supervised Semantic Segmentation for Remote Sensing Images via Multi-scale Uncertainty Consistency and Cross-Teacher-Student Attention

Semi-supervised learning offers an appealing solution for remote sensing (RS) image segmentation to relieve the burden of labor-intensive pixel-leve...