2 citations · 3 across the 5 of their papers we have counts for
5 papers
Parameter-Efficient Self-Supervised Adaptation for EEG-FM under Fixed Computational Budgets
Meghal Dani, Stefanie Liebe
EEG foundation models pretrained via self-supervised learning promise transferable representations, but their generalization remains limited, especially across diverse clinical dat…
SemioLLM: Evaluating Large Language Models for Diagnostic Reasoning from Unstructured Clinical Narratives in Epilepsy
Meghal Dani, Muthu Jeyanthi Prakash, Filip Rosa +2
Large Language Models (LLMs) have been shown to encode clinical knowledge. Many evaluations, however, rely on structured question-answer benchmarks, overlooking critical challenges…
DeViL: Decoding Vision features into Language
Meghal Dani, Isabel Rio-Torto, Stephan Alaniz +1
Post-hoc explanation methods have often been criticised for abstracting away the decision-making process of deep neural networks. In this work, we would like to provide natural lan…
An Efficient Anchor-free Universal Lesion Detection in CT-scans
Manu Sheoran, Meghal Dani, Monika Sharma +1
Existing universal lesion detection (ULD) methods utilize compute-intensive anchor-based architectures which rely on predefined anchor boxes, resulting in unsatisfactory detection…
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection
Manu Sheoran, Meghal Dani, Monika Sharma +1
Incorporating data-specific domain knowledge in deep networks explicitly can provide important cues beneficial for lesion detection and can mitigate the need for diverse heterogene…