The proceedings contain 40 papers. The topics discussed include: towards equitable kidney tumor segmentation: bias evaluation and mitigation; diffusion model-based data augmentation for lung ultrasound classification with limited data; representing visual classification as a linear combination of words; learning temporal higher-order patterns to detect anomalous brain activity; multi-modal graph learning over UMLS knowledge graphs; LLMs accelerate annotation for medical information extraction; towards reliable dermatology evaluation benchmarks; a probabilistic method to predict classifier accuracy on larger datasets given small pilot data; diffusion models to predict 3D late mechanical activation from sparse 2D cardiac MRIs; and NoteContrast: contrastive language-diagnostic pretraining for medical text.
Proceedings of the 3rd Machine Learning for Health Symposium, ML4H 2023
Parziale, Antonio;
2023-01-01
Abstract
The proceedings contain 40 papers. The topics discussed include: towards equitable kidney tumor segmentation: bias evaluation and mitigation; diffusion model-based data augmentation for lung ultrasound classification with limited data; representing visual classification as a linear combination of words; learning temporal higher-order patterns to detect anomalous brain activity; multi-modal graph learning over UMLS knowledge graphs; LLMs accelerate annotation for medical information extraction; towards reliable dermatology evaluation benchmarks; a probabilistic method to predict classifier accuracy on larger datasets given small pilot data; diffusion models to predict 3D late mechanical activation from sparse 2D cardiac MRIs; and NoteContrast: contrastive language-diagnostic pretraining for medical text.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
