Hybrid unsupervised representation learning and pseudo-label supervised self-distillation for rare disease imaging phenotype classification with dispersion-aware …
Rare diseases are characterized by low prevalence and are often chronically debilitating or
life-threatening. Imaging phenotype classification of rare diseases is challenging due to the …
life-threatening. Imaging phenotype classification of rare diseases is challenging due to the …
PneumoLLM: Harnessing the power of large language model for pneumoconiosis diagnosis
M Song, J Wang, Z Yu, J Wang, L Yang, Y Lu, B Li… - Medical Image …, 2024 - Elsevier
The conventional pretraining-and-finetuning paradigm, while effective for common diseases
with ample data, faces challenges in diagnosing data-scarce occupational diseases like …
with ample data, faces challenges in diagnosing data-scarce occupational diseases like …
A foundation model for generalizable disease diagnosis in chest X-ray images
Medical artificial intelligence (AI) is revolutionizing the interpretation of chest X-ray (CXR)
images by providing robust tools for disease diagnosis. However, the effectiveness of these …
images by providing robust tools for disease diagnosis. However, the effectiveness of these …