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.
no code implementations • BioNLP (ACL) 2022 • Liyan Tang, Shravan Kooragayalu, Yanshan Wang, Ying Ding, Greg Durrett, Justin F. Rousseau, Yifan Peng
Generating a summary from findings has been recently explored (Zhang et al., 2018, 2020) in note types such as radiology reports that typically have short length.
no code implementations • IWSLT (ACL) 2022 • Brian Yan, Patrick Fernandes, Siddharth Dalmia, Jiatong Shi, Yifan Peng, Dan Berrebbi, Xinyi Wang, Graham Neubig, Shinji Watanabe
We use additional paired Modern Standard Arabic data (MSA) to directly improve the speech recognition (ASR) and machine translation (MT) components of our cascaded systems.
no code implementations • 6 May 2024 • Rongxin Cheng, Yifan Peng, Xingda Wei, Hongrui Xie, Rong Chen, Sijie Shen, Haibo Chen
In this paper, we are the first to characterize the trade-off of performance and index size in existing SSD-based graph and cluster indexes: to improve throughput by 5. 7$\times$ and 1. 7$\times$, these indexes have to pay a 5. 8$\times$ storage amplification and 7. 7$\times$ with respect to the dataset size, respectively.
no code implementations • 4 May 2024 • Thomas Yu CHow Tam, Sonish Sivarajkumar, Sumit Kapoor, Alisa V Stolyar, Katelyn Polanska, Karleigh R McCarthy, Hunter Osterhoudt, Xizhi Wu, Shyam Visweswaran, Sunyang Fu, Piyush Mathur, Giovanni E. Cacciamani, Cong Sun, Yifan Peng, Yanshan Wang
This review provides a comprehensive overview of the human evaluation approaches used in diverse healthcare applications. This analysis examines the human evaluation of LLMs across various medical specialties, addressing factors such as evaluation dimensions, sample types, and sizes, the selection and recruitment of evaluators, frameworks and metrics, the evaluation process, and statistical analysis of the results.
1 code implementation • 30 Mar 2024 • Kanglong Fan, Wen Wen, Mu Li, Yifan Peng, Kede Ma
Panoramic videos have the advantage of providing an immersive and interactive viewing experience.
1 code implementation • 28 Mar 2024 • Song Wang, Yiliang Zhou, Ziqiang Han, Cui Tao, Yunyu Xiao, Ying Ding, Joydeep Ghosh, Yifan Peng
Data accuracy is essential for scientific research and policy development.
no code implementations • 22 Mar 2024 • Yiliang Zhou, Hanley Ong, Patrick Kennedy, Carol Wu, Jacob Kazam, Keith Hentel, Adam Flanders, George Shih, Yifan Peng
The study examines the application of GPT-4V, a multi-modal large language model equipped with visual recognition, in detecting radiological findings from a set of 100 chest radiographs and suggests that GPT-4V is currently not ready for real-world diagnostic usage in interpreting chest radiographs.
no code implementations • 19 Mar 2024 • Yishu Wei, Yu Deng, Cong Sun, Mingquan Lin, Hongmei Jiang, Yifan Peng
This scoping review aims to comprehensively review label noise management in deep learning-based medical prediction problems, which includes label noise detection, label noise handling, and evaluation.
no code implementations • 19 Mar 2024 • Yifan Peng, Ilia Kulikov, Yilin Yang, Sravya Popuri, Hui Lu, Changhan Wang, Hongyu Gong
Speech language models (LMs) are promising for high-quality speech synthesis through in-context learning.
no code implementations • 19 Mar 2024 • Yifan Peng, Ilia Kulikov, Yilin Yang, Sravya Popuri, Hui Lu, Changhan Wang, Hongyu Gong
There have been emerging research interest and advances in speech-to-speech translation (S2ST), translating utterances from one language to another.
no code implementations • 20 Feb 2024 • Yifan Peng, Yui Sudo, Muhammad Shakeel, Shinji Watanabe
Inspired by the Open Whisper-style Speech Model (OWSM) project, we propose OWSM-CTC, a novel encoder-only speech foundation model based on Connectionist Temporal Classification (CTC).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 13 Feb 2024 • Yifan Yang, Mingquan Lin, Han Zhao, Yifan Peng, Furong Huang, Zhiyong Lu
Such biases can occur before, during, or after the development of AI models, making it critical to understand and address potential biases to enable the accurate and reliable application of AI models in clinical settings.
no code implementations • 31 Jan 2024 • Yihan Wu, Soumi Maiti, Yifan Peng, Wangyou Zhang, Chenda Li, Yuyue Wang, Xihua Wang, Shinji Watanabe, Ruihua Song
Existing speech language models typically utilize task-dependent prompt tokens to unify various speech tasks in a single model.
no code implementations • 30 Jan 2024 • Yifan Peng, Jinchuan Tian, William Chen, Siddhant Arora, Brian Yan, Yui Sudo, Muhammad Shakeel, Kwanghee Choi, Jiatong Shi, Xuankai Chang, Jee-weon Jung, Shinji Watanabe
In this work, we aim to improve the performance and efficiency of OWSM without extra training data.
no code implementations • 25 Jan 2024 • Mingquan Lin, TianHao Li, Zhaoyi Sun, Gregory Holste, Ying Ding, Fei Wang, George Shih, Yifan Peng
Our proposed AI model utilizes supervised contrastive learning to minimize bias in CXR diagnosis.
1 code implementation • 22 Jan 2024 • Yuehaw Khoo, Yifan Peng, Daren Wang
In this paper, we introduce a new framework called Variance-Reduced Sketching (VRS), specifically designed to estimate density functions and nonparametric regression functions in higher dimensions with a reduced curse of dimensionality.
no code implementations • 19 Jan 2024 • Yui Sudo, Muhammad Shakeel, Yosuke Fukumoto, Yifan Peng, Shinji Watanabe
The proposed method can be trained effectively by combining a bias phrase index loss and special tokens to detect the bias phrases in the input speech data.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 16 Jan 2024 • Qiao Jin, Fangyuan Chen, Yiliang Zhou, Ziyang Xu, Justin M. Cheung, Robert Chen, Ronald M. Summers, Justin F. Rousseau, Peiyun Ni, Marc J Landsman, Sally L. Baxter, Subhi J. Al'Aref, Yijia Li, Alex Chen, Josef A. Brejt, Michael F. Chiang, Yifan Peng, Zhiyong Lu
GPT-4V also performs well in cases where physicians incorrectly answer, with over 78% accuracy.
no code implementations • 8 Jan 2024 • Gongbo Zhang, Yiliang Zhou, Yan Hu, Hua Xu, Chunhua Weng, Yifan Peng
On the PICO-Corpus, PICOX obtained higher recall and F1 scores than the baseline and improved the micro recall score from 56. 66 to 67. 33.
no code implementations • 19 Nov 2023 • Gongbo Zhang, Qiao Jin, Denis Jered McInerney, Yong Chen, Fei Wang, Curtis L. Cole, Qian Yang, Yanshan Wang, Bradley A. Malin, Mor Peleg, Byron C. Wallace, Zhiyong Lu, Chunhua Weng, Yifan Peng
Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence.
no code implementations • 24 Oct 2023 • Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen-Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng
Many real-world image recognition problems, such as diagnostic medical imaging exams, are "long-tailed" $\unicode{x2013}$ there are a few common findings followed by many more relatively rare conditions.
no code implementations • 4 Oct 2023 • Siddhant Arora, Hayato Futami, Jee-weon Jung, Yifan Peng, Roshan Sharma, Yosuke Kashiwagi, Emiru Tsunoo, Karen Livescu, Shinji Watanabe
Recent studies leverage large language models with multi-tasking capabilities, using natural language prompts to guide the model's behavior and surpassing performance of task-specific models.
Ranked #1 on Spoken Language Understanding on Fluent Speech Commands (using extra training data)
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 26 Sep 2023 • William Chen, Jiatong Shi, Brian Yan, Dan Berrebbi, Wangyou Zhang, Yifan Peng, Xuankai Chang, Soumi Maiti, Shinji Watanabe
We show that further efficiency can be achieved with a vanilla HuBERT Base model, which can maintain 94% of XLS-R's performance with only 3% of the data, 4 GPUs, and limited trials.
1 code implementation • 25 Sep 2023 • Yifan Peng, Jinchuan Tian, Brian Yan, Dan Berrebbi, Xuankai Chang, Xinjian Li, Jiatong Shi, Siddhant Arora, William Chen, Roshan Sharma, Wangyou Zhang, Yui Sudo, Muhammad Shakeel, Jee-weon Jung, Soumi Maiti, Shinji Watanabe
Pre-training speech models on large volumes of data has achieved remarkable success.
1 code implementation • 18 Sep 2023 • Chien-yu Huang, Ke-Han Lu, Shih-Heng Wang, Chi-Yuan Hsiao, Chun-Yi Kuan, Haibin Wu, Siddhant Arora, Kai-Wei Chang, Jiatong Shi, Yifan Peng, Roshan Sharma, Shinji Watanabe, Bhiksha Ramakrishnan, Shady Shehata, Hung-Yi Lee
To achieve comprehensive coverage of diverse speech tasks and harness instruction tuning, we invite the community to collaborate and contribute, facilitating the dynamic growth of the benchmark.
no code implementations • 14 Sep 2023 • Soumi Maiti, Yifan Peng, Shukjae Choi, Jee-weon Jung, Xuankai Chang, Shinji Watanabe
We propose a decoder-only language model, VoxtLM, that can perform four tasks: speech recognition, speech synthesis, text generation, and speech continuation.
1 code implementation • 17 Aug 2023 • Gregory Holste, Ziyu Jiang, Ajay Jaiswal, Maria Hanna, Shlomo Minkowitz, Alan C. Legasto, Joanna G. Escalon, Sharon Steinberger, Mark Bittman, Thomas C. Shen, Ying Ding, Ronald M. Summers, George Shih, Yifan Peng, Zhangyang Wang
This work represents a first step toward understanding the impact of pruning on model behavior in deep long-tailed, multi-label medical image classification.
no code implementations • 12 Aug 2023 • Leilei Su, Jian Chen, Yifan Peng, Cong Sun
The objective of this study is to devise a strategy that can improve the model's capability to recognize biomedical entities in scenarios of few-shot learning.
1 code implementation • 10 Aug 2023 • Haoju Leng, Ruining Deng, Shunxing Bao, Dazheng Fang, Bryan A. Millis, Yucheng Tang, Haichun Yang, Xiao Wang, Yifan Peng, Lipeng Wan, Yuankai Huo
The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario ("CPU scenario"), and (2) a GPU-based deep learning framework scenario ("GPU scenario").
no code implementations • 4 Aug 2023 • David Oniani, Jordan Hilsman, Yifan Peng, COL, Ronald K. Poropatich, COL Jeremy C. Pamplin, LTC Gary L. Legault, Yanshan Wang
In 2020, the U. S. Department of Defense officially disclosed a set of ethical principles to guide the use of Artificial Intelligence (AI) technologies on future battlefields.
no code implementations • 14 Jul 2023 • Zhaoyi Sun, Mingquan Lin, Qingqing Zhu, Qianqian Xie, Fei Wang, Zhiyong Lu, Yifan Peng
In this scoping review, we aim to provide a comprehensive overview of the current state of the field and identify key concepts, types of studies, and research gaps with a focus on biomedical images and texts joint learning, mainly because these two were the most commonly available data types in MDL research.
no code implementations • 29 Jun 2023 • Haoxuan Xu, Zeyu He, Mengfan Shen, Songning Lai, Ziqiang Han, Yifan Peng
Experiments show that the proposed method achieves state-of-the-art results on the present dataset.
no code implementations • 20 Jun 2023 • Mingquan Lin, Song Wang, Ying Ding, Lihui Zhao, Fei Wang, Yifan Peng
Background: The predictive Intensive Care Unit (ICU) scoring system plays an important role in ICU management because it predicts important outcomes, especially mortality.
1 code implementation • 14 Jun 2023 • Qingqing Zhu, Tejas Sudharshan Mathai, Pritam Mukherjee, Yifan Peng, Ronald M. Summers, Zhiyong Lu
Pre-filling a radiology report holds promise in mitigating reporting errors, and despite efforts in the literature to generate medical reports, there exists a lack of approaches that exploit the longitudinal nature of patient visit records in the MIMIC-CXR dataset.
no code implementations • 11 Jun 2023 • William Chen, Xuankai Chang, Yifan Peng, Zhaoheng Ni, Soumi Maiti, Shinji Watanabe
Our code and training optimizations make SSL feasible with only 8 GPUs, instead of the 32 used in the original work.
no code implementations • 2 Jun 2023 • Yosuke Kashiwagi, Siddhant Arora, Hayato Futami, Jessica Huynh, Shih-Lun Wu, Yifan Peng, Brian Yan, Emiru Tsunoo, Shinji Watanabe
We reduce the model size by applying tensor decomposition to the Conformer and E-Branchformer architectures used in our E2E SLU models.
no code implementations • 30 May 2023 • Liyan Tang, Yifan Peng, Yanshan Wang, Ying Ding, Greg Durrett, Justin F. Rousseau
To tackle this problem, we propose a controlled text generation method that uses a novel contrastive learning strategy to encourage models to differentiate between generating likely and less likely outputs according to humans.
1 code implementation • 28 May 2023 • Yifan Peng, Yui Sudo, Shakeel Muhammad, Shinji Watanabe
Knowledge distillation trains a small student model to mimic the behavior of a large teacher model.
2 code implementations • 18 May 2023 • Yifan Peng, Kwangyoun Kim, Felix Wu, Brian Yan, Siddhant Arora, William Chen, Jiyang Tang, Suwon Shon, Prashant Sridhar, Shinji Watanabe
Conformer, a convolution-augmented Transformer variant, has become the de facto encoder architecture for speech processing due to its superior performance in various tasks, including automatic speech recognition (ASR), speech translation (ST) and spoken language understanding (SLU).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 2 May 2023 • Hayato Futami, Jessica Huynh, Siddhant Arora, Shih-Lun Wu, Yosuke Kashiwagi, Yifan Peng, Brian Yan, Emiru Tsunoo, Shinji Watanabe
In the track, we adopt a pipeline approach of ASR and NLU.
no code implementations • 2 May 2023 • Siddhant Arora, Hayato Futami, Shih-Lun Wu, Jessica Huynh, Yifan Peng, Yosuke Kashiwagi, Emiru Tsunoo, Brian Yan, Shinji Watanabe
Recently there have been efforts to introduce new benchmark tasks for spoken language understanding (SLU), like semantic parsing.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 11 Apr 2023 • Yifan Peng, Yian Chen, E. Miles Stoudenmire, Yuehaw Khoo
We propose a hierarchical tensor-network approach for approximating high-dimensional probability density via empirical distribution.
1 code implementation • 10 Apr 2023 • Brian Yan, Jiatong Shi, Yun Tang, Hirofumi Inaguma, Yifan Peng, Siddharth Dalmia, Peter Polák, Patrick Fernandes, Dan Berrebbi, Tomoki Hayashi, Xiaohui Zhang, Zhaoheng Ni, Moto Hira, Soumi Maiti, Juan Pino, Shinji Watanabe
ESPnet-ST-v2 is a revamp of the open-source ESPnet-ST toolkit necessitated by the broadening interests of the spoken language translation community.
1 code implementation • ICCV 2023 • Xiaoyang Lyu, Peng Dai, Zizhang Li, Dongyu Yan, Yi Lin, Yifan Peng, Xiaojuan Qi
We found that the color rendering loss results in optimization bias against low-intensity areas, causing gradient vanishing and leaving these areas unoptimized.
no code implementations • 15 Mar 2023 • Qianqian Xie, Jiayu Zhou, Yifan Peng, Fei Wang
We propose to extract medical facts of the input medical report, its gold summary, and candidate summaries based on the RadGraph schema and design the fact-guided reranker to efficiently incorporate the extracted medical facts for selecting the optimal summary.
1 code implementation • 14 Mar 2023 • Yifan Peng, Jaesong Lee, Shinji Watanabe
Transformer-based end-to-end speech recognition has achieved great success.
1 code implementation • 27 Feb 2023 • Yifan Peng, Kwangyoun Kim, Felix Wu, Prashant Sridhar, Shinji Watanabe
Self-supervised speech representation learning (SSL) has shown to be effective in various downstream tasks, but SSL models are usually large and slow.
1 code implementation • 24 Feb 2023 • William Chen, Brian Yan, Jiatong Shi, Yifan Peng, Soumi Maiti, Shinji Watanabe
In this paper, we introduce our work on improving performance on FLEURS, a 102-language open ASR benchmark, by conditioning the entire model on language identity (LID).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 26 Jan 2023 • Mingquan Lin, Yuyun Xiao, BoJian Hou, Tingyi Wanyan, Mohit Manoj Sharma, Zhangyang Wang, Fei Wang, Sarah Van Tassel, Yifan Peng
In the United States, primary open-angle glaucoma (POAG) is the leading cause of blindness, especially among African American and Hispanic individuals.
2 code implementations • 8 Dec 2022 • Soumi Maiti, Yifan Peng, Takaaki Saeki, Shinji Watanabe
While human evaluation is the most reliable metric for evaluating speech generation systems, it is generally costly and time-consuming.
no code implementations • 6 Dec 2022 • Zehao Yu, Xi Yang, Chong Dang, Prakash Adekkanattu, Braja Gopal Patra, Yifan Peng, Jyotishman Pathak, Debbie L. Wilson, Ching-Yuan Chang, Wei-Hsuan Lo-Ciganic, Thomas J. George, William R. Hogan, Yi Guo, Jiang Bian, Yonghui Wu
Objective: We aim to develop an open-source natural language processing (NLP) package, SODA (i. e., SOcial DeterminAnts), with pre-trained transformer models to extract social determinants of health (SDoH) for cancer patients, examine the generalizability of SODA to a new disease domain (i. e., opioid use), and evaluate the extraction rate of SDoH using cancer populations.
no code implementations • 6 Dec 2022 • Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang
However, DNNs are notoriously fragile to the class imbalance in image classification.
no code implementations • 10 Nov 2022 • Yifan Peng, Siddhant Arora, Yosuke Higuchi, Yushi Ueda, Sujay Kumar, Karthik Ganesan, Siddharth Dalmia, Xuankai Chang, Shinji Watanabe
Collecting sufficient labeled data for spoken language understanding (SLU) is expensive and time-consuming.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +6
no code implementations • 15 Oct 2022 • Ajay Jaiswal, Kumar Ashutosh, Justin F Rousseau, Yifan Peng, Zhangyang Wang, Ying Ding
Our extensive experiments on popular medical imaging classification tasks (cardiopulmonary disease and lesion classification) using real-world datasets, show the performance benefit of RoS-KD, its ability to distill knowledge from many popular large networks (ResNet-50, DenseNet-121, MobileNet-V2) in a comparatively small network, and its robustness to adversarial attacks (PGD, FSGM).
1 code implementation • 30 Sep 2022 • Kwangyoun Kim, Felix Wu, Yifan Peng, Jing Pan, Prashant Sridhar, Kyu J. Han, Shinji Watanabe
Conformer, combining convolution and self-attention sequentially to capture both local and global information, has shown remarkable performance and is currently regarded as the state-of-the-art for automatic speech recognition (ASR).
Ranked #9 on Speech Recognition on LibriSpeech test-other
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
1 code implementation • 29 Aug 2022 • Gregory Holste, Song Wang, Ziyu Jiang, Thomas C. Shen, George Shih, Ronald M. Summers, Yifan Peng, Zhangyang Wang
Imaging exams, such as chest radiography, will yield a small set of common findings and a much larger set of uncommon findings.
Ranked #1 on Long-tail Learning on MIMIC-CXR-LT
1 code implementation • 10 Jul 2022 • Yan Han, Gregory Holste, Ying Ding, Ahmed Tewfik, Yifan Peng, Zhangyang Wang
Using the learned self-attention of its image branch, RGT extracts a bounding box for which to compute radiomic features, which are further processed by the radiomics branch; learned image and radiomic features are then fused and mutually interact via cross-attention layers.
4 code implementations • 6 Jul 2022 • Yifan Peng, Siddharth Dalmia, Ian Lane, Shinji Watanabe
Conformer has proven to be effective in many speech processing tasks.
no code implementations • 55th Hawaii International Conference on System Sciences 2022 • Suzanna Schmeelk, Martins Samuel Dogo, Yifan Peng, Braja Gopal Patra
Clinical notes, which can be embedded into electronic medical records, document patient care delivery and summarize interactions between healthcare providers and patients.
1 code implementation • 19 Mar 2022 • Song Wang, Mingquan Lin, Ying Ding, George Shih, Zhiyong Lu, Yifan Peng
Analyzing radiology reports is a time-consuming and error-prone task, which raises the need for an efficient automated radiology report analysis system to alleviate the workloads of radiologists and encourage precise diagnosis.
no code implementations • 11 Jan 2022 • Song Wang, Liyan Tang, Mingquan Lin, George Shih, Ying Ding, Yifan Peng
In this work, we propose to mine and represent the associations among medical findings in an informative knowledge graph and incorporate this prior knowledge with radiology report generation to help improve the quality of generated reports.
2 code implementations • 29 Nov 2021 • Siddhant Arora, Siddharth Dalmia, Pavel Denisov, Xuankai Chang, Yushi Ueda, Yifan Peng, Yuekai Zhang, Sujay Kumar, Karthik Ganesan, Brian Yan, Ngoc Thang Vu, Alan W Black, Shinji Watanabe
However, there are few open source toolkits that can be used to generate reproducible results on different Spoken Language Understanding (SLU) benchmarks.
1 code implementation • 11 Nov 2021 • Mehmet Efruz Karabulut, K. Vijay-Shanker, Yifan Peng
Our system obtained 0. 7708 in precision and 0. 7770 in recall, for an F1 score of 0. 7739, demonstrating the effectiveness of using ensembles of BERT-based language models for automatically detecting relations between chemicals and proteins.
no code implementations • 9 Nov 2021 • Tejas Sudharshan Mathai, SungWon Lee, Daniel C. Elton, Thomas C. Shen, Yifan Peng, Zhiyong Lu, Ronald M. Summers
Identification of lymph nodes (LN) in T2 Magnetic Resonance Imaging (MRI) is an important step performed by radiologists during the assessment of lymphoproliferative diseases.
no code implementations • 28 Oct 2021 • Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin Rousseau, Yifan Peng, Ying Ding
Radiology reports are unstructured and contain the imaging findings and corresponding diagnoses transcribed by radiologists which include clinical facts and negated and/or uncertain statements.
no code implementations • 27 Oct 2021 • Ajay Jaiswal, TianHao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding
In this paper, we proposed a novel and simple data augmentation method based on patient metadata and supervised knowledge to create clinically accurate positive and negative augmentations for chest X-rays.
no code implementations • 29 Sep 2021 • Yan Han, Ying Ding, Ahmed Tewfik, Yifan Peng, Zhangyang Wang
During training, the image branch leverages its learned attention to estimate pathology localization, which is then utilized to extract radiomic features from images in the radiomics branch.
1 code implementation • 4 Sep 2021 • Zhanghexuan Ji, Mohammad Abuzar Shaikh, Dana Moukheiber, Sargur Srihari, Yifan Peng, Mingchen Gao
Self-supervised learning provides an opportunity to explore unlabeled chest X-rays and their associated free-text reports accumulated in clinical routine without manual supervision.
no code implementations • 27 Aug 2021 • Yitao Shen, Yue Wang, Xingyu Lu, Feng Qi, Jia Yan, Yixiang Mu, Yao Yang, Yifan Peng, Jinjie Gu
In order to do effective optimization in the second stage, counterfactual prediction and noise-reduction are essential for the first stage.
1 code implementation • NAACL 2021 • Hyun Gi Lee, Evan Sholle, Ashley Beecy, Subhi Al'Aref, Yifan Peng
Utilizing clinical texts in survival analysis is difficult because they are largely unstructured.
1 code implementation • NAACL (BioNLP) 2021 • Peng Su, Yifan Peng, K. Vijay-Shanker
In this work, we explore the method of employing contrastive learning to improve the text representation from the BERT model for relation extraction.
no code implementations • 11 Apr 2021 • Yan Han, Chongyan Chen, Ahmed Tewfik, Benjamin Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
The key knob of our framework is a unique positive sampling approach tailored for the medical images, by seamlessly integrating radiomic features as a knowledge augmentation.
no code implementations • 12 Jan 2021 • Yan Han, Chongyan Chen, Ahmed H Tewfik, Ying Ding, Yifan Peng
Traditionally, radiomics, as a subfield of radiology that can extract a large number of quantitative features from medical images, demonstrates its potential to facilitate medical imaging diagnosis before the deep learning era.
no code implementations • 17 Dec 2020 • Hongya Song, Yaoguang Ma, Yubing Han, Weidong Shen, Wenyi Zhang, Yanghui Li, Xu Liu, Yifan Peng, Xiang Hao
Computational spectroscopic instruments with Broadband Encoding Stochastic (BEST) filters allow the reconstruction of the spectrum at high precision with only a few filters.
Instrumentation and Detectors
no code implementations • 25 Nov 2020 • Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Song Wang, Ahmed Tewfik, George Shih, Ying Ding, Yifan Peng
After a number of iterations and with the help of radiomic features, our framework can converge to more accurate image regions.
no code implementations • 9 Nov 2020 • Qingyu Chen, Tiarnan D. L. Keenan, Alexis Allot, Yifan Peng, Elvira Agrón, Amitha Domalpally, Caroline C. W. Klaver, Daniel T. Luttikhuizen, Marcus H. Colyer, Catherine A. Cukras, Henry E. Wiley, M. Teresa Magone, Chantal Cousineau-Krieger, Wai T. Wong, Yingying Zhu, Emily Y. Chew, Zhiyong Lu
The objective was to develop and evaluate the performance of a novel 'M3' deep learning framework on RPD detection.
1 code implementation • 11 Oct 2020 • Yifan Peng, Lin Lin, Lexing Ying, Leonardo Zepeda-Núñez
We showcase this framework by introducing a neural network architecture that combines LRC-layers with short-range convolutional layers to accurately learn the energy and force associated with a $N$-body potential.
no code implementations • 7 Aug 2020 • Lana Yeganova, Rezarta Islamaj, Qingyu Chen, Robert Leaman, Alexis Allot, Chin-Hsuan Wei, Donald C. Comeau, Won Kim, Yifan Peng, W. John Wilbur, Zhiyong Lu
In this study we analyze the LitCovid collection, 13, 369 COVID-19 related articles found in PubMed as of May 15th, 2020 with the purpose of examining the landscape of literature and presenting it in a format that facilitates information navigation and understanding.
no code implementations • 19 Jul 2020 • Yifan Peng, Tiarnan D. Keenan, Qingyu Chen, Elvira Agrón, Alexis Allot, Wai T. Wong, Emily Y. Chew, Zhiyong Lu
By 2040, age-related macular degeneration (AMD) will affect approximately 288 million people worldwide.
1 code implementation • 11 Jun 2020 • Yifan Peng, Yu-Xing Tang, Sung-Won Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu
(1) We show that COVID-19-CT-CXR, when used as additional training data, is able to contribute to improved DL performance for the classification of COVID-19 and non-COVID-19 CT. (2) We collected CT images of influenza and trained a DL baseline to distinguish a diagnosis of COVID-19, influenza, or normal or other types of diseases on CT. (3) We trained an unsupervised one-class classifier from non-COVID-19 CXR and performed anomaly detection to detect COVID-19 CXR.
1 code implementation • WS 2020 • Yifan Peng, Qingyu Chen, Zhiyong Lu
Multi-task learning (MTL) has achieved remarkable success in natural language processing applications.
14 code implementations • 12 Aug 2019 • Ke Yan, You-Bao Tang, Yifan Peng, Veit Sandfort, Mohammadhadi Bagheri, Zhiyong Lu, Ronald M. Summers
When reading medical images such as a computed tomography (CT) scan, radiologists generally search across the image to find lesions, characterize and measure them, and then describe them in the radiological report.
Ranked #7 on Medical Object Detection on DeepLesion
no code implementations • CVPR 2020 • Christopher A. Metzler, Hayato Ikoma, Yifan Peng, Gordon Wetzstein
High-dynamic-range (HDR) imaging is crucial for many computer graphics and vision applications.
1 code implementation • 7 Jun 2019 • Tiarnan D. Keenan, Shazia Dharssi, Yifan Peng, Qingyu Chen, Elvira Agrón, Wai T. Wong, Zhiyong Lu, Emily Y. Chew
Results: The deep learning models (GA detection, CGA detection from all eyes, and centrality detection from GA eyes) had AUC of 0. 933-0. 976, 0. 939-0. 976, and 0. 827-0. 888, respectively.
no code implementations • 30 Apr 2019 • Yifan Peng, Ke Yan, Veit Sandfort, Ronald M. Summers, Zhiyong Lu
In radiology, radiologists not only detect lesions from the medical image, but also describe them with various attributes such as their type, location, size, shape, and intensity.
3 code implementations • CVPR 2019 • Ke Yan, Yifan Peng, Veit Sandfort, Mohammadhadi Bagheri, Zhiyong Lu, Ronald M. Summers
In radiologists' routine work, one major task is to read a medical image, e. g., a CT scan, find significant lesions, and describe them in the radiology report.
no code implementations • 4 Mar 2019 • Ke Yan, Yifan Peng, Zhiyong Lu, Ronald M. Summers
To address this problem, we define a set of 145 labels based on RadLex to describe a large variety of lesions in the DeepLesion dataset.
no code implementations • 21 Jan 2019 • Alistair E. W. Johnson, Tom J. Pollard, Nathaniel R. Greenbaum, Matthew P. Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G. Mark, Seth J. Berkowitz, Steven Horng
Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's thorax, but requiring specialized training for proper interpretation.
no code implementations • 2 Dec 2018 • Qingyu Chen, Yifan Peng, Tiarnan Keenan, Shazia Dharssi, Elvira Agron, Wai T. Wong, Emily Y. Chew, Zhiyong Lu
Built on our previous work DeepSeeNet, we developed a novel deep learning model for automated classification of images into the 9-step scale.
Age-Related Macular Degeneration Classification Classification +2
1 code implementation • 19 Nov 2018 • Yifan Peng, Shazia Dharssi, Qingyu Chen, Tiarnan D. Keenan, Elvira Agrón, Wai T. Wong, Emily Y. Chew, Zhiyong Lu
DeepSeeNet simulates the human grading process by first detecting individual AMD risk factors (drusen size, pigmentary abnormalities) for each eye and then calculating a patient-based AMD severity score using the AREDS Simplified Severity Scale.
4 code implementations • 13 Nov 2018 • Jingcheng Du, Qingyu Chen, Yifan Peng, Yang Xiang, Cui Tao, Zhiyong Lu
Due to this nature, the multi-label text classification task is often considered to be more challenging compared to the binary or multi-class text classification problems.
4 code implementations • 22 Oct 2018 • Qingyu Chen, Yifan Peng, Zhiyong Lu
Sentence embeddings have become an essential part of today's natural language processing (NLP) systems, especially together advanced deep learning methods.
Ranked #1 on Sentence Embeddings For Biomedical Texts on MedSTS (using extra training data)
no code implementations • CVPR 2018 • Qilin Sun, Xiong Dun, Yifan Peng, Wolfgang Heidrich
Time-of-flight depth imaging and transient imaging are two imaging modalities that have recently received a lot of interest.
no code implementations • 5 Feb 2018 • Yifan Peng, Anthony Rios, Ramakanth Kavuluru, Zhiyong Lu
Text mining the relations between chemicals and proteins is an increasingly important task.
no code implementations • CVPR 2018 • Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Ronald M. Summers
Chest X-rays are one of the most common radiological examinations in daily clinical routines.
no code implementations • 5 Jan 2018 • Xiaoran Wang, Yifan Peng, Benwen Zhang
One way to make software development more efficient is to make the program more readable.
Software Engineering
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 • ICCV 2017 • Tiancheng Sun, Yifan Peng, Wolfgang Heidrich
Image aberrations can cause severe degradation in image quality for consumer-level cameras, especially under the current tendency to reduce the complexity of lens designs in order to shrink the overall size of modules.
no code implementations • WS 2017 • Rezarta Islamaj Do{\u{g}}an, Andrew Chatr-aryamontri, Sun Kim, Chih-Hsuan Wei, Yifan Peng, Donald Comeau, Zhiyong Lu
The Precision Medicine Track in BioCre-ative VI aims to bring together the Bi-oNLP community for a novel challenge focused on mining the biomedical litera-ture in search of mutations and protein-protein interactions (PPI).
no code implementations • WS 2017 • Yifan Peng, Zhiyong Lu
State-of-the-art methods for protein-protein interaction (PPI) extraction are primarily feature-based or kernel-based by leveraging lexical and syntactic information.
25 code implementations • CVPR 2017 • Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, Ronald M. Summers
The chest X-ray is one of the most commonly accessible radiological examinations for screening and diagnosis of many lung diseases.
no code implementations • CVPR 2013 • Kiwon Yun, Yifan Peng, Dimitris Samaras, Gregory J. Zelinsky, Tamara L. Berg
We posit that user behavior during natural viewing of images contains an abundance of information about the content of images as well as information related to user intent and user defined content importance.