Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical
  Visual Question Answering   Medical visual question answering (Med-VQA) has tremendous potential in
healthcare. However, the development of this technology is hindered by the
lacking of publicly-available and high-quality labeled datasets for training
and evaluation. In this paper, we present a large bilingual dataset, SLAKE,
with comprehensive semantic labels annotated by experienced physicians and a
new structural medical knowledge base for Med-VQA. Besides, SLAKE includes
richer modalities and covers more human body parts than the currently available
dataset. We show that SLAKE can be used to facilitate the development and
evaluation of Med-VQA systems. The dataset can be downloaded from
http://www.med-vqa.com/slake.

17
The categories of this paper are: q-fin
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn