no code implementations • 15 Mar 2024 • Zhixiu Lu, Hailong Li, Lili He
The integration of artificial intelligence (AI) with radiology has marked a transformative era in medical diagnostics.
no code implementations • 22 Dec 2023 • Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Mekibib Altaye, Kim M. Cecil, Nehal A. Parikh, Lili He
The integration of different imaging modalities, such as structural, diffusion tensor, and functional magnetic resonance imaging, with deep learning models has yielded promising outcomes in discerning phenotypic characteristics and enhancing disease diagnosis.
no code implementations • 18 Sep 2023 • Jiatai Wang, Zhiwei Xu, Xuewen Yang, Hailong Li, Bo Li, Xuying Meng
However, as contrastive learning continues to evolve within the field of computer vision, self-supervised learning has also made substantial research progress and is progressively becoming dominant in MVC methods.
1 code implementation • 20 Feb 2023 • Zhiyuan Li, Hailong Li, Anca L. Ralescu, Jonathan R. Dillman, Nehal A. Parikh, Lili He
We compared our proposed method with other state-of-the-art self-supervised learning methods on a simulation study and two independent datasets.
no code implementations • 8 Feb 2022 • Zhiyuan Li, Hailong Li, Adebayo Braimah, Jonathan R. Dillman, Nehal A. Parikh, Lili He
We applied the OAP-EL to predict cognitive deficits at 2 years of age using quantitative brain maturation and geometric features obtained at term equivalent age in very preterm infants.
no code implementations • 28 Jul 2018 • Jiyang Xie, Jiaxin Guo, Zhanyu Ma, Jing-Hao Xue, Qie Sun, Hailong Li, Jun Guo
ENN and ARIMA are used to predict seasonal and trend components, respectively.