134 citations · 159 across the 10 of their papers we have counts for
10 papers
Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine
Qiao Jin, Fangyuan Chen, Yiliang Zhou +15
Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily…
Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses
Liyan Tang, Yifan Peng, Yanshan Wang +3
A human decision-maker benefits the most from an AI assistant that corrects for their biases. For problems such as generating interpretation of a radiology report given findings, a…
Analyzing Impact of Socio-Economic Factors on COVID-19 Mortality Prediction Using SHAP Value
Redoan Rahman, Jooyeong Kang, Justin F Rousseau +1
This paper applies multiple machine learning (ML) algorithms to a dataset of de-identified COVID-19 patients provided by the COVID-19 Research Database. The dataset consists of 20,…
Using Explainable AI to Cross-Validate Socio-economic Disparities Among Covid-19 Patient Mortality
Li Shi, Redoan Rahman, Esther Melamed +3
This paper applies eXplainable Artificial Intelligence (XAI) methods to investigate the socioeconomic disparities in COVID patient mortality. An Extreme Gradient Boosting (XGBoost)…
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances
Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau +3
Deep neural networks (DNNs) have rapidly become a \textit{de facto} choice for medical image understanding tasks. However, DNNs are notoriously fragile to the class imbalance in im…
RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging
Ajay Jaiswal, Kumar Ashutosh, Justin F Rousseau +3
AI-powered Medical Imaging has recently achieved enormous attention due to its ability to provide fast-paced healthcare diagnoses. However, it usually suffers from a lack of high-q…
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again
Ajay Jaiswal, Peihao Wang, Tianlong Chen +3
Despite the enormous success of Graph Convolutional Networks (GCNs) in modeling graph-structured data, most of the current GCNs are shallow due to the notoriously challenging probl…
Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors
Liyan Tang, Tanya Goyal, Alexander R. Fabbri +6
The propensity of abstractive summarization models to make factual errors has been studied extensively, including design of metrics to detect factual errors and annotation of error…
SCALP -- Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata
Ajay Jaiswal, Tianhao Li, Cyprian Zander +4
Computer-aided diagnosis plays a salient role in more accessible and accurate cardiopulmonary diseases classification and localization on chest radiography. Millions of people get…
Building a PubMed knowledge graph
Jian Xu, Sunkyu Kim, Min Song +12
PubMed is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguated, which has significantly hindered knowledge discovery.…