Wei‐Hung Weng

Learning Deep Representations of Medical Images using Siamese CNNs with Application to Content-Based Image Retrieval

2017 · arXiv (Cornell University)

Deep neural networks have been investigated in learning latent representations of medical images, yet most of the studies limit their approach in a single supervised convolutional neural network (CNN), which usually rely heavily on a …

PRAG: Paninian Retrieval-Augmented Generation for Safety-Critical Medical Question Answering

2020 · arXiv (Cornell University)

Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present the first free-form multiple-choice OpenQA dataset for solving medical …

What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

2021 · Preprints.org

Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present the first free-form multiple-choice OpenQA dataset for solving medical …

Publicly Available Clinical BERT Embeddings

2019 · arXiv (Cornell University)

Contextual word embedding models such as ELMo (Peters et al., 2018) and BERT (Devlin et al., 2018) have dramatically improved performance for many natural language processing (NLP) tasks in recent months. However, these models have …

Publicly Available Clinical

2019

Contextual word embedding models such as ELMo and BERT have dramatically improved performance for many natural language processing (NLP) tasks in recent months. However, these models have been minimally explored on specialty corpora, such as …