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Open-Ended Medical VQA Through Prefix Tuning of Language Models

Medical Visual Question Answering (VQA) is an important challenge, as it would lead to faster and more accurate diagnoses and treatment decisions. Most existing methods approach it as a multi-class classification problem, which restricts the outcome to a predefined closed-set of curated answers.

Data and Resources

Cite this as

Tom van Sonsbeek, Mohammad Mahdi Derakhshani, Ivona Najdenkoska, Cees G. M. Snoek, Marcel Worring (2024). Dataset: Open-Ended Medical VQA Through Prefix Tuning of Language Models. https://doi.org/10.57702/7wgskel5

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.2303.05977
Author Tom van Sonsbeek
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Mohammad Mahdi Derakhshani
Ivona Najdenkoska
Cees G. M. Snoek
Marcel Worring
Homepage https://github.com/tjvsonsbeek/open-ended-medical-vqa