# Knowledge-Aware Neural Networks for Medical Forum Question Classification

arXiv: https://arxiv.org/abs/2109.13141 · HTML: https://mlsanity.com/paper/2109.13141/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 33 references that are in the map.
- First posted on arXiv 27 Sep 2021.

## Builds on (most cited first, 15 of 15)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Deep contextualized word representations](https://mlsanity.com/paper/1802.05365/) (2018)
- [BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://mlsanity.com/paper/1901.08746/) (2019)
- [Convolutional Neural Networks for Sentence Classification](https://mlsanity.com/paper/1408.5882/) (2014)
- [Bag of Tricks for Efficient Text Classification](https://mlsanity.com/paper/1607.01759/) (2016)
- [Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge](https://mlsanity.com/paper/1805.07858/) (2018)
- [Leveraging Knowledge Bases in LSTMs for Improving Machine Reading](https://mlsanity.com/paper/1902.09091/) (2019)
- [A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extraction](https://mlsanity.com/paper/1912.07976/) (2019)
- [Language Modeling Teaches You More Syntax than Translation Does: Lessons Learned Through Auxiliary Task Analysis](https://mlsanity.com/paper/1809.10040/) (2018)
- [Fast and Effective Biomedical Entity Linking Using a Dual Encoder](https://mlsanity.com/paper/2103.05028/) (2021)
- [Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing](https://mlsanity.com/paper/1802.05930/) (2018)
- [Dynamic Integration of Background Knowledge in Neural NLU Systems](https://mlsanity.com/paper/1706.02596/) (2017)
- [Automatically Assessing Quality of Online Health Articles](https://mlsanity.com/paper/2004.05113/) (2020)

## Abstract (arXiv)

Online medical forums have become a predominant platform for answering health-related information needs of consumers. However, with a significant rise in the number of queries and the limited availability of experts, it is necessary to automatically classify medical queries based on a consumer's intention, so that these questions may be directed to the right set of medical experts. Here, we develop a novel medical knowledge-aware BERT-based model (MedBERT) that explicitly gives more weightage to medical concept-bearing words, and utilize domain-specific side information obtained from a popular medical knowledge base. We also contribute a multi-label dataset for the Medical Forum Question Classification (MFQC) task. MedBERT achieves state-of-the-art performance on two benchmark datasets and performs very well in low resource settings.