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pro vyhledávání: '"Arcucci"'
Autor:
Liu, Che, Wan, Zhongwei, Wang, Haozhe, Chen, Yinda, Qaiser, Talha, Jin, Chen, Yousefi, Fariba, Burlutskiy, Nikolay, Arcucci, Rossella
Medical Vision-Language Pre-training (MedVLP) has made significant progress in enabling zero-shot tasks for medical image understanding. However, training MedVLP models typically requires large-scale datasets with paired, high-quality image-text data
Externí odkaz:
http://arxiv.org/abs/2410.13523
Advancements in Multimodal Large Language Models (MLLMs) have significantly improved medical task performance, such as Visual Question Answering (VQA) and Report Generation (RG). However, the fairness of these models across diverse demographic groups
Externí odkaz:
http://arxiv.org/abs/2410.01089
How Does Diverse Interpretability of Textual Prompts Impact Medical Vision-Language Zero-Shot Tasks?
Recent advancements in medical vision-language pre-training (MedVLP) have significantly enhanced zero-shot medical vision tasks such as image classification by leveraging large-scale medical image-text pair pre-training. However, the performance of t
Externí odkaz:
http://arxiv.org/abs/2409.00543
Data assimilation techniques are often confronted with challenges handling complex high dimensional physical systems, because high precision simulation in complex high dimensional physical systems is computationally expensive and the exact observatio
Externí odkaz:
http://arxiv.org/abs/2409.00244
Global wildfire models play a crucial role in anticipating and responding to changing wildfire regimes. JULES-INFERNO is a global vegetation and fire model simulating wildfire emissions and area burnt on a global scale. However, because of the high d
Externí odkaz:
http://arxiv.org/abs/2409.00237
Autor:
Liu, Che, Wan, Zhongwei, Wang, Yuqi, Shen, Hui, Wang, Haozhe, Zheng, Kangyu, Zhang, Mi, Arcucci, Rossella
Automatic radiology report generation can significantly benefit the labor-intensive process of report writing by radiologists, especially for 3D radiographs like CT scans, which are crucial for broad clinical diagnostics yet underexplored compared to
Externí odkaz:
http://arxiv.org/abs/2406.07146
Hyperspectral data acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) have allowed for unparalleled mapping of the surface mineralogy of Mars. Due to sensor degradation over time, a significant portion of the recently acquir
Externí odkaz:
http://arxiv.org/abs/2403.17757
The burgeoning integration of 3D medical imaging into healthcare has led to a substantial increase in the workload of medical professionals. To assist clinicians in their diagnostic processes and alleviate their workload, the development of a robust
Externí odkaz:
http://arxiv.org/abs/2403.15992
Electrocardiograms (ECGs) are non-invasive diagnostic tools crucial for detecting cardiac arrhythmic diseases in clinical practice. While ECG Self-supervised Learning (eSSL) methods show promise in representation learning from unannotated ECG data, t
Externí odkaz:
http://arxiv.org/abs/2403.06659
Autor:
Wan, Zhongwei, Liu, Che, Wang, Xin, Tao, Chaofan, Shen, Hui, Peng, Zhenwu, Fu, Jie, Arcucci, Rossella, Yao, Huaxiu, Zhang, Mi
Electrocardiogram (ECG) is the primary non-invasive diagnostic tool for monitoring cardiac conditions and is crucial in assisting clinicians. Recent studies have concentrated on classifying cardiac conditions using ECG data but have overlooked ECG re
Externí odkaz:
http://arxiv.org/abs/2403.04945