Pain Management

ACCORD: Alleviating Concept Coupling through Dependence Regularization for Text-to-Image Diffusion Personalization

Image personalization has garnered attention for its ability to customize Text-to-Image generation using only a few reference images. However, a key challenge in image personalization is the issue of conceptual coupling, where the limited number of reference images leads the model to form unwanted associations between the personalization target and other concepts. Current methods attempt to tack...

LightEndoStereo: A Real-time Lightweight Stereo Matching Method for Endoscopy Images

Real-time acquisition of accurate depth of scene is essential for automated robotic minimally invasive surgery, and stereo matching with binocular endoscopy can generate such depth. However, existing algorithms struggle with ambiguous tissue boundaries and real-time performance in prevalent high-resolution endoscopic scenes. We propose LightEndoStereo, a lightweight real-time stereo matching met...

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices

Laplacian matrices are commonly employed in many real applications, encoding the underlying latent structural information such as graphs and manifol...

A Multidimensional Regression Model for Predicting Recurrence in Chronic Low Back Pain.

BACKGROUND: Recurrence is common in chronic low back pain (CLBP). However, predicting the recurrence risk remains a challenge. The aim is to develop a...

Developing and validating a prediction tool for cerebral amyloid angiopathy neuropathological severity.

INTRODUCTION: Cerebral amyloid angiopathy (CAA) is a cerebrovascular condition, the severity of which can only be determined post mortem. Here, we dev...

Towards artificial intelligence application in pain medicine.

Pain is a complex, multidimensional experience involving significant challenges in both diagnosis and management. While acute pain serves as a critica...

Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response Prediction

Neuropathic pain, affecting up to 10% of adults, remains difficult to treat due to limited therapeutic efficacy and tolerability. Although resting-s...

Autoregressive Medical Image Segmentation via Next-Scale Mask Prediction

While deep learning has significantly advanced medical image segmentation, most existing methods still struggle with handling complex anatomical reg...

GONet: A Generalizable Deep Learning Model for Glaucoma Detection

Glaucomatous optic neuropathy (GON) is a prevalent ocular disease that can lead to irreversible vision loss if not detected early and treated. The t...

ImageChain: Advancing Sequential Image-to-Text Reasoning in Multimodal Large Language Models

Reasoning over sequences of images remains a challenge for multimodal large language models (MLLMs). While recent models incorporate multi-image dat...

Nonlinear Sparse Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data

Motivation: Biomedical studies increasingly produce multi-view high-dimensional datasets (e.g., multi-omics) that demand integrative analysis. Exist...

A Novel Spatiotemporal Correlation Anomaly Detection Method Based on Time-Frequency-Domain Feature Fusion and a Dynamic Graph Neural Network in Wireless Sensor Network

Attention-based transformers have played an important role in wireless sensor network (WSN) timing anomaly detection due to their ability to capture...

Fundus2Globe: Generative AI-Driven 3D Digital Twins for Personalized Myopia Management

Myopia, projected to affect 50% population globally by 2050, is a leading cause of vision loss. Eyes with pathological myopia exhibit distinctive sh...

Hardware-Software Co-Design for Accelerating Transformer Inference Leveraging Compute-in-Memory

Transformers have become the backbone of neural network architecture for most machine learning applications. Their widespread use has resulted in mu...

Language Complexity Measurement as a Noisy Zero-Shot Proxy for Evaluating LLM Performance

Large Language Models (LLMs) have made significant strides in natural language generation but often face challenges in tasks requiring precise calcu...

Multi-scale Masked Autoencoder for Electrocardiogram Anomaly Detection

Electrocardiogram (ECG) analysis is a fundamental tool for diagnosing cardiovascular conditions, yet anomaly detection in ECG signals remains challe...

L2GNet: Optimal Local-to-Global Representation of Anatomical Structures for Generalized Medical Image Segmentation

Continuous Latent Space (CLS) and Discrete Latent Space (DLS) models, like AttnUNet and VQUNet, have excelled in medical image segmentation. In cont...

TFBS-Finder: Deep Learning-based Model with DNABERT and Convolutional Networks to Predict Transcription Factor Binding Sites

Transcription factors are proteins that regulate the expression of genes by binding to specific genomic regions known as Transcription Factor Bindin...

Optimizing Feature Selection in Causal Inference: A Three-Stage Computational Framework for Unbiased Estimation

Feature selection is an important but challenging task in causal inference for obtaining unbiased estimates of causal quantities. Properly selected ...

A machine learning approach to automate microinfarct and microhemorrhage screening in hematoxylin and eosin-stained human brain tissues.

Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no o...