1 citations · 1 across the 7 of their papers we have counts for
8 papers
RadJEPA: Radiology Encoder for Chest X-Rays via Joint Embedding Predictive Architecture
Anas Anwarul Haq Khan, Mariam Husain, Pratik Jalan +1
Vision-language pretraining has driven progress in medical image representation learning, but it depends on paired image-text data and can inherit reporting bias from clinical narr…
Broken Words, Broken Performance: Effect of Tokenization on Performance of LLMs
Sachin Pawar, Manoj Apte, Kshitij Jadhav +2
Tokenization is the first step in training any Large Language Model (LLM), where the text is split into a sequence of tokens as per the model's fixed vocabulary. This tokenization…
Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models
Deval Mehta, Yiwen Jiang, Catherine L Jan +3
Recent advancements in deep learning have shown significant potential for classifying retinal diseases using color fundus images. However, existing works predominantly rely exclusi…
IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework
Anurag Shandilya, Swapnil Bhat, Akshat Gautam +4
Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-ta…
MIRAGE: Multimodal Identification and Recognition of Annotations in Indian General Prescriptions
Tavish Mankash, V. S. Chaithanya Kota, Anish De +2
Hospitals in India still rely on handwritten medical records despite the availability of Electronic Medical Records (EMR), complicating statistical analysis and record retrieval. H…
PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learning
Sarang Galada, Tanurima Halder, Kunal Deo +2
Multi-site MRI studies often suffer from site-specific variations arising from differences in methodology, hardware, and acquisition protocols, thereby compromising accuracy and re…
One Shot GANs for Long Tail Problem in Skin Lesion Dataset using novel content space assessment metric
Kunal Deo, Deval Mehta, Kshitij Jadhav
Long tail problems frequently arise in the medical field, particularly due to the scarcity of medical data for rare conditions. This scarcity often leads to models overfitting on s…
Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification
Raja Kumar, Raghav Singhal, Pranamya Kulkarni +2
Deep multimodal learning has shown remarkable success by leveraging contrastive learning to capture explicit one-to-one relations across modalities. However, real-world data often…