no code implementations • 29 Apr 2024 • Halid Ziya Yerebakan, Yoshihisa Shinagawa, Gerardo Hermosillo Valadez
Organ segmentation is a fundamental task in medical imaging, and it is useful for many clinical automation pipelines.
no code implementations • 19 Sep 2023 • Yikuan Li, Hanyin Wang, Halid Yerebakan, Yoshihisa Shinagawa, Yuan Luo
In this study, we investigated the ability of the large language model (LLM) to enhance healthcare data interoperability.
no code implementations • 11 Aug 2023 • Halid Ziya Yerebakan, Yoshihisa Shinagawa, Mahesh Ranganath, Simon Allen-Raffl, Gerardo Hermosillo Valadez
We propose a method to match anatomical locations between pairs of medical images in longitudinal comparisons.
1 code implementation • 5 Oct 2022 • Xiongchao Chen, Yoshihisa Shinagawa, Zhigang Peng, Gerardo Hermosillo Valadez
Magnetic resonance imaging (MRI) is one of the most commonly applied tests in neurology and neurosurgery.
no code implementations • 23 Jun 2020 • Halid Ziya Yerebakan, Parmeet Bhatia, Yoshihisa Shinagawa
We have shown that the method creates interpretable projections of original embedding dimensions.
no code implementations • COLING 2018 • Halid Ziya Yerebakan, Yoshihisa Shinagawa, Parmeet Bhatia, Yiqiang Zhan
To facilitate this, we have used a representation learning algorithm that creates a semantic representation space for documents where the clinically related documents lie close to each other.
no code implementations • 20 Jan 2016 • Halid Ziya Yerebakan, Fitsum Reda, Yiqiang Zhan, Yoshihisa Shinagawa
This paper presents a new Bayesian non-parametric model by extending the usage of Hierarchical Dirichlet Allocation to extract tree structured word clusters from text data.