no code implementations • 18 Sep 2023 • Reza Shirkavand, Heng Huang
We propose a novel approach called deep graph prompt tuning as an alternative to fine-tuning for leveraging large graph transformer models in downstream graph based prediction tasks.
no code implementations • 1 Jun 2023 • Reza Shirkavand, Fei Zhang, Heng Huang
This work highlights the potential of deep learning techniques, specifically transformer-based models, in revolutionizing the healthcare industry's approach to postoperative care.
no code implementations • 25 May 2023 • Reza Shirkavand, Liang Zhan, Heng Huang, Li Shen, Paul M. Thompson
Especially in studies of brain diseases, research cohorts may include both neuroimaging data and genetic data, but for practical clinical diagnosis, we often need to make disease predictions only based on neuroimages.
no code implementations • 18 Mar 2021 • Reza Shirkavand, Sana Ayromlou, Soroush Farghadani, Maedeh-sadat Tahaei, Fattane Pourakpour, Bahareh Siahlou, Zeynab Khodakarami, Mohammad H. Rohban, Mansoor Fatehi, Hamid R. Rabiee
Fazekas scale facilitates an accurate quantitative assessment of the severity of white matter lesions and hence the disease.