58 citations · 70 across the 9 of their papers we have counts for
9 papers
Video-Instrument Synergistic Network for Referring Video Instrument Segmentation in Robotic Surgery
Hongqiu Wang, Lei Zhu, Guang Yang +4
Robot-assisted surgery has made significant progress, with instrument segmentation being a critical factor in surgical intervention quality. It serves as the building block to faci…
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…
Suggestive Annotation of Brain MR Images with Gradient-guided Sampling
Chengliang Dai, Shuo Wang, Yuanhan Mo +3
Machine learning has been widely adopted for medical image analysis in recent years given its promising performance in image segmentation and classification tasks. The success of m…
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…
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
OmiTrans: generative adversarial networks based omics-to-omics translation framework
Xiaoyu Zhang, Yike Guo
With the rapid development of high-throughput experimental technologies, different types of omics (e.g., genomics, epigenomics, transcriptomics, proteomics, and metabolomics) data…
Clinical Utility of the Automatic Phenotype Annotation in Unstructured Clinical Notes: ICU Use Cases
Jingqing Zhang, Luis Bolanos, Ashwani Tanwar +3
Objective: Clinical notes contain information not present elsewhere, including drug response and symptoms, all of which are highly important when predicting key outcomes in acute c…
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…