982 citations · 1.1k across the 12 of their papers we have counts for
12 papers
The Potential and Pitfalls of using a Large Language Model such as ChatGPT or GPT-4 as a Clinical Assistant
Jingqing Zhang, Kai Sun, Akshay Jagadeesh +5
Recent studies have demonstrated promising performance of ChatGPT and GPT-4 on several medical domain tasks. However, none have assessed its performance using a large-scale real-wo…
A Scalable Workflow to Build Machine Learning Classifiers with Clinician-in-the-Loop to Identify Patients in Specific Diseases
Jingqing Zhang, Atri Sharma, Luis Bolanos +4
Clinicians may rely on medical coding systems such as International Classification of Diseases (ICD) to identify patients with diseases from Electronic Health Records (EHRs). Howev…
Medical Scientific Table-to-Text Generation with Human-in-the-Loop under the Data Sparsity Constraint
Heng-Yi Wu, Jingqing Zhang, Julia Ive +4
Structured (tabular) data in the preclinical and clinical domains contains valuable information about individuals and an efficient table-to-text summarization system can drasticall…
Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge
Ashwani Tanwar, Jingqing Zhang, Julia Ive +2
Extracting phenotypes from clinical text has been shown to be useful for a variety of clinical use cases such as identifying patients with rare diseases. However, reasoning with nu…
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh +1
Recent work pre-training Transformers with self-supervised objectives on large text corpora has shown great success when fine-tuned on downstream NLP tasks including text summariza…
Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records
Jingqing Zhang, Xiaoyu Zhang, Kai Sun +3
The extraction of phenotype information which is naturally contained in electronic health records (EHRs) has been found to be useful in various clinical informatics applications su…
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification
Xiaoyu Zhang, Jingqing Zhang, Kai Sun +3
Different aspects of a clinical sample can be revealed by multiple types of omics data. Integrated analysis of multi-omics data provides a comprehensive view of patients, which has…
Exclusion in Junction Geometries
K. Zhang, P. L. Krapivsky, S. Redner
We investigate the dynamics of the asymmetric exclusion process at a junction. When two input roads are initially fully occupied and a single output road is initially empty, the en…
Integrating Semantic Knowledge to Tackle Zero-shot Text Classification
Jingqing Zhang, Piyawat Lertvittayakumjorn, Yike Guo
Insufficient or even unavailable training data of emerging classes is a big challenge of many classification tasks, including text classification. Recognising text documents of cla…
Deep Sequence Learning with Auxiliary Information for Traffic Prediction
Binbing Liao, Jingqing Zhang, Chao Wu +5
Predicting traffic conditions from online route queries is a challenging task as there are many complicated interactions over the roads and crowds involved. In this paper, we inten…
The Deep Poincaré Map: A Novel Approach for Left Ventricle Segmentation
Yuanhan Mo, Fangde Liu, Douglas McIlwraith +4
Precise segmentation of the left ventricle (LV) within cardiac MRI images is a prerequisite for the quantitative measurement of heart function. However, this task is challenging du…
I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation
Hao Dong, Jingqing Zhang, Douglas McIlwraith +1
Translating information between text and image is a fundamental problem in artificial intelligence that connects natural language processing and computer vision. In the past few ye…