Jianbo Yuan

TL;DR: In this article, a generative encoder-decoder model was proposed to generate radiology reports from chest X-ray images and reports with the following improvements: first, the encoder was pre-trained with a large number of chest images to accurately recognize 14 common radiographic observations, while taking advantage of the multi-view images by enforcing the cross-view consistency.

TL;DR: A generative encoder-decoder model is proposed and extracted medical concepts based on the radiology reports in the training data and fine-tune the encoder to extract the most frequent medical concepts from the x-ray images.

TL;DR: This paper proposed a novel scheme for Twitter sentiment analysis with extra attention on emojis, where they first learn bi-sense emoji embeddings under positive and negative sentimental tweets individually, and then train a sentiment classifier by attending on these bi-semi-emojis embedding with an attention-based LSTM.

TL;DR: A Dynamic Graph-Based Spatial-Temporal Attention (DG-STA) method for hand gesture recognition to first construct a fully-connected graph from a hand skeleton, where the node features and edges are automatically learned via a self-attention mechanism that performs in both spatial and temporal domains.