Search Results for author: Qiao Jin

Found 28 papers, 10 papers with code

Benchmarking Retrieval-Augmented Generation for Medicine

2 code implementations20 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.

Benchmarking Information Retrieval +2

AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning

no code implementations20 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.

Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science

no code implementations6 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.

Harnessing PubMed User Query Logs for Post Hoc Explanations of Recommended Similar Articles

no code implementations5 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.

Recommendation Systems

Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for Radiology Reports

no code implementations29 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.

Sentence Text Generation

Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation

no code implementations25 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.

Medical Report Generation

PubTator 3.0: an AI-powered Literature Resource for Unlocking Biomedical Knowledge

no code implementations19 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.

Navigate Relation

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.

Matching Patients to Clinical Trials with Large Language Models

1 code implementation27 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.

Language Modelling Large Language Model

PubMed and Beyond: Biomedical Literature Search in the Age of Artificial Intelligence

no code implementations18 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.

Less Can Be More: Exploring Population Rating Dispositions with Partitioned Models in Recommender Systems

no code implementations20 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.

Computational Efficiency Recommendation Systems

GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information

1 code implementation19 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.

In-Context Learning Retrieval

LADER: Log-Augmented DEnse Retrieval for Biomedical Literature Search

no code implementations10 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.


RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training

1 code implementation1 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.

Question Answering Retrieval +1

PMC-Patients: A Large-scale Dataset of Patient Summaries and Relations for Benchmarking Retrieval-based Clinical Decision Support Systems

2 code implementations28 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.

Benchmarking Retrieval

DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction

1 code implementation31 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.

graph construction Knowledge Graphs +4

Predicting Clinical Trial Results by Implicit Evidence Integration

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.


Probing Biomedical Embeddings from Language Models

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.

NER Word Embeddings

Neural Models for Reasoning over Multiple Mentions using Coreference

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.


Cannot find the paper you are looking for? You can Submit a new open access paper.