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arXiv · 2203.02932

Doctor Recommendation in Online Health Forums via Expertise Learning

Xiaoxin Lu·Yubo Zhang·Jing Li·Shi Zong
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Abstract

Huge volumes of patient queries are daily generated on online health forums, rendering manual doctor allocation a labor-intensive task. To better help patients, this paper studies a novel task of doctor recommendation to enable automatic pairing of a patient to a doctor with relevant expertise. While most prior work in recommendation focuses on modeling target users from their past behavior, we can only rely on the limited words in a query to infer a patient's needs for privacy reasons. For doctor modeling, we study the joint effects of their profiles and previous dialogues with other patients and explore their interactions via self-learning. The learned doctor embeddings are further employed to estimate their capabilities of handling a patient query with a multi-head attention mechanism. For experiments, a large-scale dataset is collected from Chunyu Yisheng, a Chinese online health forum, where our model exhibits the state-of-the-art results, outperforming baselines only consider profiles and past dialogues to characterize a doctor.

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Xiaoxin Lu, Yubo Zhang, Jing Li, Shi Zong. 2022-03-06. Doctor Recommendation in Online Health Forums via Expertise Learning. https://arxiv.org/abs/2203.02932

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