1 code implementation • EMNLP (ClinicalNLP) 2020 • Yifan Peng, SungWon Lee, Daniel C. Elton, Thomas Shen, Yu-Xing Tang, Qingyu Chen, Shuai Wang, Yingying Zhu, Ronald Summers, Zhiyong Lu
We then introduce an end-to-end approach based on the combination of rules and transformer-based methods to detect these abdominal lymph node mentions and classify their types from the MRI radiology reports.
1 code implementation • 6 Mar 2024 • Ricardo Bigolin Lanfredi, Pritam Mukherjee, Ronald Summers
Additionally, using these improved annotations in classification supervision, we demonstrate substantial advancements in model quality, with an increase of 1. 7 pp in AUROC over models trained with annotations from the state-of-the-art approach.
1 code implementation • 5 Jul 2021 • Benjamin Hou, Georgios Kaissis, Ronald Summers, Bernhard Kainz
Chest radiographs are one of the most common diagnostic modalities in clinical routine.
1 code implementation • 16 Dec 2017 • Yifan Peng, Xiaosong Wang, Le Lu, Mohammadhadi Bagheri, Ronald Summers, Zhiyong Lu
Negative and uncertain medical findings are frequent in radiology reports, but discriminating them from positive findings remains challenging for information extraction.
no code implementations • CVPR 2018 • Ke Yan, Xiaosong Wang, Le Lu, Ling Zhang, Adam Harrison, Mohammadhad Bagheri, Ronald Summers
Then, a triplet network is utilized to learn lesion embeddings with a sequential sampling strategy to depict their hierarchical similarity structure.
no code implementations • 25 Mar 2016 • Xiaosong Wang, Le Lu, Hoo-chang Shin, Lauren Kim, Isabella Nogues, Jianhua Yao, Ronald Summers
Obtaining semantic labels on a large scale radiology image database (215, 786 key images from 61, 845 unique patients) is a prerequisite yet bottleneck to train highly effective deep convolutional neural network (CNN) models for image recognition.