Search Results for author: Yifan Peng

Found 97 papers, 37 papers with code

Automatic recognition of abdominal lymph nodes from clinical text

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.

CMU’s IWSLT 2022 Dialect Speech Translation System

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.

Knowledge Distillation Machine Translation +3

EchoGen: Generating Conclusions from Echocardiogram Notes

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.


OWSM-CTC: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identification

no code implementations20 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) +4

A survey of recent methods for addressing AI fairness and bias in biomedicine

no code implementations13 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.


Nonparametric Estimation via Variance-Reduced Sketching

1 code implementation22 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.

Density Estimation regression

Contextualized Automatic Speech Recognition with Attention-Based Bias Phrase Boosted Beam Search

no code implementations19 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

A Span-based Model for Extracting Overlapping PICO Entities from RCT Publications

no code implementations8 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.

Data Augmentation PICO

Leveraging Generative AI for Clinical Evidence Summarization Needs to Ensure Trustworthiness

no code implementations19 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.

Joint Prediction and Denoising for Large-scale Multilingual Self-supervised Learning

no code implementations26 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.

Denoising Self-Supervised Learning

Dynamic-SUPERB: Towards A Dynamic, Collaborative, and Comprehensive Instruction-Tuning Benchmark for Speech

1 code implementation18 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.

Voxtlm: unified decoder-only models for consolidating speech recognition/synthesis and speech/text continuation tasks

no code implementations14 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.

Language Modelling speech-recognition +3

Demonstration-based learning for few-shot biomedical named entity recognition under machine reading comprehension

no code implementations12 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.

Few-Shot Learning Machine Reading Comprehension +2

High-performance Data Management for Whole Slide Image Analysis in Digital Pathology

1 code implementation10 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").

Management whole slide images

From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence

no code implementations4 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.

Decision Making

A scoping review on multimodal deep learning in biomedical images and texts

no code implementations14 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.

Cross-Modal Retrieval Decision Making +5

Classifying Crime Types using Judgment Documents from Social Media

no code implementations29 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.

An empirical study of using radiology reports and images to improve ICU mortality prediction

no code implementations20 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.

ICU Mortality Management +1

Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports

1 code implementation14 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.

speech-recognition Speech Recognition

Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses

no code implementations30 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.

Contrastive Learning Decision Making +1

A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks

2 code implementations18 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

Generative Modeling via Hierarchical Tensor Sketching

no code implementations11 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.

Learning a Room with the Occ-SDF Hybrid: Signed Distance Function Mingled with Occupancy Aids Scene Representation

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.

Neural Rendering Surface Reconstruction

FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization

no code implementations15 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.

Graph Generation

Structured Pruning of Self-Supervised Pre-trained Models for Speech Recognition and Understanding

1 code implementation27 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.

Model Compression Representation Learning +2

Improving Massively Multilingual ASR With Auxiliary CTC Objectives

1 code implementation24 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

SpeechLMScore: Evaluating speech generation using speech language model

2 code implementations8 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.

Language Modelling Speech Enhancement +1

SODA: A Natural Language Processing Package to Extract Social Determinants of Health for Cancer Studies

no code implementations6 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.

RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging

no code implementations15 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).

Classification Knowledge Distillation +1

E-Branchformer: Branchformer with Enhanced merging for speech recognition

1 code implementation30 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).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays

1 code implementation10 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.

Radiology Text Analysis System (RadText): Architecture and Evaluation

1 code implementation19 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.

De-identification named-entity-recognition +5

Prior Knowledge Enhances Radiology Report Generation

no code implementations11 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.

ESPnet-SLU: Advancing Spoken Language Understanding through ESPnet

2 code implementations29 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.

Spoken Language Understanding

CU-UD: text-mining drug and chemical-protein interactions with ensembles of BERT-based models

1 code implementation11 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.


Lymph Node Detection in T2 MRI with Transformers

no code implementations9 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.

RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification

no code implementations28 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.

Classification Contrastive Learning

SCALP -- Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata

no code implementations27 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.

Contrastive Learning Data Augmentation

CheXT: Knowledge-Guided Cross-Attention Transformer for Abnormality Classification and Localization in Chest X-rays

no code implementations29 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.

Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment

1 code implementation4 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.

Representation Learning Self-Supervised Learning +1

A framework for massive scale personalized promotion

no code implementations27 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.


Improving BERT Model Using Contrastive Learning for Biomedical Relation Extraction

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.

Contrastive Learning Data Augmentation +2

Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop

no code implementations11 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.

Contrastive Learning

Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning

no code implementations12 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.

Contrastive Learning Pneumonia Detection

Deep-Learned Broadband Encoding Stochastic Filters for Computational Spectroscopic Instruments

no code implementations17 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

Efficient Long-Range Convolutions for Point Clouds

1 code implementation11 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.

Navigating the landscape of COVID-19 research through literature analysis: A bird's eye view

no code implementations7 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.

Clustering named-entity-recognition +2

COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature

1 code implementation11 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.

Anomaly Detection Computed Tomography (CT) +1

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

14 code implementations12 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.

Computed Tomography (CT) Lesion Detection +2

A deep learning approach for automated detection of geographic atrophy from color fundus photographs

1 code implementation7 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.


A self-attention based deep learning method for lesion attribute detection from CT reports

no code implementations30 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.

Attribute Sentence

Fine-grained lesion annotation in CT images with knowledge mined from radiology reports

no code implementations4 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.

Sentence Test

MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

no code implementations21 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.

DeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs

1 code implementation19 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.

Decision Making General Classification

ML-Net: multi-label classification of biomedical texts with deep neural networks

4 code implementations13 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.

Benchmarking Feature Engineering +4

BioSentVec: creating sentence embeddings for biomedical texts

4 code implementations22 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)

Benchmarking Sentence +2

Depth and Transient Imaging With Compressive SPAD Array Cameras

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.

Compressive Sensing

Comment Generation for Source Code: State of the Art, Challenges and Opportunities

no code implementations5 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

NegBio: a high-performance tool for negation and uncertainty detection in radiology reports

1 code implementation16 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.

Benchmarking Negation

Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction

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.

BioCreative VI Precision Medicine Track: creating a training corpus for mining protein-protein interactions affected by mutations

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).

Relation Extraction

Deep learning for extracting protein-protein interactions from biomedical literature

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.

Benchmarking Cross-corpus +2

Studying Relationships between Human Gaze, Description, and Computer Vision

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.

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