no code implementations • NAACL 2018 • Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov
Many problems in NLP require aggregating information from multiple mentions of the same entity which may be far apart in the text.
Ranked #7 on Question Answering on WikiHop
no code implementations • WS 2018 • Qiao Jin, Bhuwan Dhingra, William Cohen, Xinghua Lu
There are millions of articles in PubMed database.
1 code implementation • WS 2019 • Qiao Jin, Bhuwan Dhingra, William W. Cohen, Xinghua Lu
For this we use the pre-trained LMs as fixed feature extractors and restrict the downstream task models to not have additional sequence modeling layers.
no code implementations • WS 2019 • Qiao Jin, Jinling Liu, Xinghua Lu
Abbreviation Expansion (DECBAE) model.
3 code implementations • IJCNLP 2019 • Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W. Cohen, Xinghua Lu
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts.
Ranked #7 on Question Answering on PubMedQA
1 code implementation • EMNLP 2020 • Qiao Jin, Chuanqi Tan, Mosha Chen, Xiaozhong Liu, Songfang Huang
In the CTRP framework, a model takes a PICO-formatted clinical trial proposal with its background as input and predicts the result, i. e. how the Intervention group compares with the Comparison group in terms of the measured Outcome in the studied Population.
no code implementations • 10 Feb 2021 • Qiao Jin, Zheng Yuan, Guangzhi Xiong, Qianlan Yu, Huaiyuan Ying, Chuanqi Tan, Mosha Chen, Songfang Huang, Xiaozhong Liu, Sheng Yu
Automatic Question Answering (QA) has been successfully applied in various domains such as search engines and chatbots.
1 code implementation • 31 May 2021 • Dejie Chang, Mosha Chen, Chaozhen Liu, LiPing Liu, Dongdong Li, Wei Li, Fei Kong, Bangchang Liu, Xiaobin Luo, Ji Qi, Qiao Jin, Bin Xu
In order to accelerate the research for domain-specific knowledge graphs in the medical domain, we introduce DiaKG, a high-quality Chinese dataset for Diabetes knowledge graph, which contains 22, 050 entities and 6, 890 relations in total.
2 code implementations • 28 Feb 2022 • Zhengyun Zhao, Qiao Jin, Fangyuan Chen, Tuorui Peng, Sheng Yu
Results: PMC-Patients contains 167k patient summaries with 3. 1M patient-article relevance annotations and 293k patient-patient similarity annotations, which is the largest-scale resource for ReCDS and also one of the largest patient collections.
1 code implementation • 1 Mar 2023 • Zheng Yuan, Qiao Jin, Chuanqi Tan, Zhengyun Zhao, Hongyi Yuan, Fei Huang, Songfang Huang
We propose to retrieve similar image-text pairs based on ITC from pretraining datasets and introduce a novel retrieval-attention module to fuse the representation of the image and the question with the retrieved images and texts.
no code implementations • 10 Apr 2023 • Qiao Jin, Andrew Shin, Zhiyong Lu
On all queries, LADER can improve the performance of a dense retriever by 24%-37% relative NDCG@10 while not requiring additional training, and further performance improvement is expected from more logs.
1 code implementation • 19 Apr 2023 • Qiao Jin, Yifan Yang, Qingyu Chen, Zhiyong Lu
In this paper, we present GeneGPT, a novel method for teaching LLMs to use the Web APIs of the National Center for Biotechnology Information (NCBI) for answering genomics questions.
no code implementations • 15 Jun 2023 • Shubo Tian, Qiao Jin, Lana Yeganova, Po-Ting Lai, Qingqing Zhu, Xiuying Chen, Yifan Yang, Qingyu Chen, Won Kim, Donald C. Comeau, Rezarta Islamaj, Aadit Kapoor, Xin Gao, Zhiyong Lu
In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health.
no code implementations • 20 Jun 2023 • Ruixuan Sun, Ruoyan Kong, Qiao Jin, Joseph A. Konstan
In this study, we partition users by rating disposition - looking first at their percentage of negative ratings, and then at the general use of the rating scale.
2 code implementations • 2 Jul 2023 • Qiao Jin, Won Kim, Qingyu Chen, Donald C. Comeau, Lana Yeganova, W. John Wilbur, Zhiyong Lu
In response, we introduce MedCPT, a first-of-its-kind Contrastively Pre-trained Transformer model for zero-shot semantic IR in biomedicine.
no code implementations • 18 Jul 2023 • Qiao Jin, Robert Leaman, Zhiyong Lu
In response, we present a survey of literature search tools tailored to both general and specific information needs in biomedicine, with the objective of helping readers efficiently fulfill their information needs.
1 code implementation • 27 Jul 2023 • Qiao Jin, Zifeng Wang, Charalampos S. Floudas, Fangyuan Chen, Changlin Gong, Dara Bracken-Clarke, Elisabetta Xue, Yifan Yang, Jimeng Sun, Zhiyong Lu
Given a patient note, TrialGPT predicts the patient's eligibility on a criterion-by-criterion basis and then consolidates these predictions to assess the patient's eligibility for the target trial.
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 • 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 • 19 Jan 2024 • Chih-Hsuan Wei, Alexis Allot, Po-Ting Lai, Robert Leaman, Shubo Tian, Ling Luo, Qiao Jin, Zhizheng Wang, Qingyu Chen, Zhiyong Lu
PubTator 3. 0 (https://www. ncbi. nlm. nih. gov/research/pubtator3/) is a biomedical literature resource using state-of-the-art AI techniques to offer semantic and relation searches for key concepts like proteins, genetic variants, diseases, and chemicals.
no code implementations • 23 Jan 2024 • Zhe He, Balu Bhasuran, Qiao Jin, Shubo Tian, Karim Hanna, Cindy Shavor, Lisbeth Garcia Arguello, Patrick Murray, Zhiyong Lu
Lab results are often confusing and hard to understand.
no code implementations • 25 Jan 2024 • Yifan Yang, Xiaoyu Liu, Qiao Jin, Furong Huang, Zhiyong Lu
Large language models like GPT-3. 5-turbo and GPT-4 hold promise for healthcare professionals, but they may inadvertently inherit biases during their training, potentially affecting their utility in medical applications.
no code implementations • 29 Jan 2024 • Qingqing Zhu, Xiuying Chen, Qiao Jin, Benjamin Hou, Tejas Sudharshan Mathai, Pritam Mukherjee, Xin Gao, Ronald M Summers, Zhiyong Lu
In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging.
no code implementations • 5 Feb 2024 • Ashley Shin, Qiao Jin, James Anibal, Zhiyong Lu
Our study suggests that repurposing user query logs of academic search engines can be a promising way to train state-of-the-art models for explaining literature recommendation.
no code implementations • 6 Feb 2024 • Xiangru Tang, Qiao Jin, Kunlun Zhu, Tongxin Yuan, Yichi Zhang, Wangchunshu Zhou, Meng Qu, Yilun Zhao, Jian Tang, Zhuosheng Zhang, Arman Cohan, Zhiyong Lu, Mark Gerstein
Intelligent agents powered by large language models (LLMs) have demonstrated substantial promise in autonomously conducting experiments and facilitating scientific discoveries across various disciplines.
no code implementations • 20 Feb 2024 • Qiao Jin, Zhizheng Wang, Yifan Yang, Qingqing Zhu, Donald Wright, Thomas Huang, W John Wilbur, Zhe He, Andrew Taylor, Qingyu Chen, Zhiyong Lu
Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis.
2 code implementations • 20 Feb 2024 • Guangzhi Xiong, Qiao Jin, Zhiyong Lu, Aidong Zhang
However, a RAG system can involve multiple flexible components, and there is a lack of best practices regarding the optimal RAG setting for various medical purposes.
no code implementations • 8 Mar 2024 • Qingqing Zhu, Benjamin Hou, Tejas S. Mathai, Pritam Mukherjee, Qiao Jin, Xiuying Chen, Zhizheng Wang, Ruida Cheng, Ronald M. Summers, Zhiyong Lu
The volume of CT exams being done in the world has been rising every year, which has led to radiologist burn-out.