Transplantation

Improving Heart Rejection Detection in XPCI Images Using Synthetic Data Augmentation

Accurate identification of acute cellular rejection (ACR) in endomyocardial biopsies is essential for effective management of heart transplant patients. However, the rarity of high-grade rejection cases (3R) presents a significant challenge for training robust deep learning models. This work addresses the class imbalance problem by leveraging synthetic data generation using StyleGAN to augment t...

Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration, exhibits limited sensitivity to conventional radiochemotherapy. Although immunotherapy has shown efficacy in some patients, its applicability is not universally effective. Studies have indicated that programmed cell death (PCD) can modulate the activity of immune cells and participate in the regula...

Prediction of Drug-Induced Nephrotoxicity Using Chemical Information and Transcriptomics Data.

Prediction of drug-induced nephrotoxicity is an important task in the drug discovery and development pipeline. Chemical information-based machine lear...

A Real-Analytic Approach to Differential-Algebraic Dynamic Logic

This paper introduces a proof calculus for real-analytic differential-algebraic dynamic logic, enabling correct transformations of differential-alge...

[New technologies serve as accelerators for breakthroughs in modern acupuncture research].

As one of China's most internationally influential original disciplines, acupuncture-moxibustion has a development history of over 2 000 years. The fo...

TK-Mamba: Marrying KAN with Mamba for Text-Driven 3D Medical Image Segmentation

3D medical image segmentation is vital for clinical diagnosis and treatment but is challenged by high-dimensional data and complex spatial dependenc...

CENet: Context Enhancement Network for Medical Image Segmentation

Medical image segmentation, particularly in multi-domain scenarios, requires precise preservation of anatomical structures across diverse representa...

RemoteSAM: Towards Segment Anything for Earth Observation

We aim to develop a robust yet flexible visual foundation model for Earth observation. It should possess strong capabilities in recognizing and loca...

RemoteSAM: Towards Segment Anything for Earth Observation

We aim to develop a robust yet flexible visual foundation model for Earth observation. It should possess strong capabilities in recognizing and loca...

Semantic segmentation with reward

In real-world scenarios, pixel-level labeling is not always available. Sometimes, we need a semantic segmentation network, and even a visual encoder...

EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion

Medical image classification is critical for clinical decision-making, yet demands for accuracy, interpretability, and generalizability remain chall...

EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion

Medical image classification is critical for clinical decision-making, yet demands for accuracy, interpretability, and generalizability remain chall...

SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis

Survival analysis, which estimates the probability of event occurrence over time from censored data, is fundamental in numerous real-world applicati...

Latent Flow Transformer

Transformers, the standard implementation for large language models (LLMs), typically consist of tens to hundreds of discrete layers. While more lay...

s3: You Don't Need That Much Data to Train a Search Agent via RL

Retrieval-augmented generation (RAG) systems empower large language models (LLMs) to access external knowledge during inference. Recent advances hav...

[Application and prospect of artificial intelligence in the field of occupational hygiene].

Artificial intelligence technology has been applied in occupational hazards monitoring, occupational health risks prediction and occupational disease ...

Context-aware data augmentation for enhanced speech command recognition in industrial environments.

In Human-Robot Interaction, speech is one of the most intuitive and effective communication channel. In Industry 4.0, speech-based communication can s...

Balancing accuracy and cost in machine learning models for detecting medial vascular calcification in chronic kidney disease: a pilot study.

Machine learning algorithms that integrate multiple biomarkers are increasingly used in disease detection, yet economic considerations are often overl...

Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates.

Therapeutic hypothermia (TH) significantly reduces mortality and morbidities in neonates with Neonatal Encephalopathy (NE). NE may result in neonatal ...

Kornia-rs: A Low-Level 3D Computer Vision Library In Rust

We present \textit{kornia-rs}, a high-performance 3D computer vision library written entirely in native Rust, designed for safety-critical and real-...