982 citations · 1.1k across the 12 of their papers we have counts for
7 papers · 1 filter
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…
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…