14 papers
Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys
Zeyu Xia, Kan Ma, Sibo Cheng +7
The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcing phases. Chromium-based sup…
A Probabilistic Approach to Wildfire Spread Prediction Using a Denoising Diffusion Surrogate Model
Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn +3
Thanks to recent advances in generative AI, computers can now simulate realistic and complex natural processes. We apply this capability to predict how wildfires spread, a task mad…
SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning
Mingsheng Cai, Jiuming Jiang, Wenhao Huang +2
Cardiovascular diseases are a leading cause of death and disability worldwide. Electrocardiogram (ECG) is critical for diagnosing and monitoring cardiac health, but obtaining large…
Knowledge to Sight: Reasoning over Visual Attributes via Knowledge Decomposition for Abnormality Grounding
Jun Li, Che Liu, Wenjia Bai +4
In this work, we address the problem of grounding abnormalities in medical images, where the goal is to localize clinical findings based on textual descriptions. While generalist V…
How Far Have Medical Vision-Language Models Come? A Comprehensive Benchmarking Study
Che Liu, Jiazhen Pan, Weixiang Shen +3
Vision-Language Models (VLMs) trained on web-scale corpora excel at natural image tasks and are increasingly repurposed for healthcare; however, their competence in medical tasks r…
MEIT: Multimodal Electrocardiogram Instruction Tuning on Large Language Models for Report Generation
Zhongwei Wan, Che Liu, Xin Wang +6
Electrocardiogram (ECG) is the primary non-invasive diagnostic tool for monitoring cardiac conditions and is crucial in assisting clinicians. Recent studies have concentrated on cl…