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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (9): 88-97    DOI: 10.11925/infotech.2096-3467.2019.0147
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Automatic Triage of Online Doctor Services Based on Machine Learning
Ruojia Wang1,2,Lu Zhang1,Jimin Wang1()
1 Department of Information Management, Peking University, Beijing 100871, China
2 Institute of Ocean Research, Peking University, Beijing 100871, China
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Abstract  

[Objective] This paper compares the performance of various machine learning algorithms for automatic triage, aiming to improve their effectiveness through analyzing mis-classification data. [Methods] First, we retrieved 33,073 real patients’ questions from a website named “chunyu doctor”. Then, we compared the accuracy of two text vectorization methods and six classification models. Finally, we analyzed the mis-classification data and extracted new features to improve the performance of models. [Results] The best automatic triage model used TF-IDF as text vectorization method and support vector machine as classification algorithm. After adding age and gender characteristics, the classification accuracy rate reached 76.3%. The classifier had the lowest accuracy rate for surgery department due to the setting of this platform’s categories. [Limitations] We assumed that the department selection of the patient was correct. [Conclusions] Machine learning techniques could improve the performance of automatic triage services of the online health consulting platforms.

Key wordsAsk the Doctor Service      Automatic Triage      Machine Learning      Support Vector Machine     
Received: 11 February 2019      Published: 23 October 2019
ZTFLH:  TP393 G35  

Cite this article:

Ruojia Wang,Lu Zhang,Jimin Wang. Automatic Triage of Online Doctor Services Based on Machine Learning. Data Analysis and Knowledge Discovery, 2019, 3(9): 88-97.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2019.0147     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I9/88

科室 示例 样本数(个)
内科 我的心跳最近跳的次数在九十跳左右算正常吗 3 405
外科 60岁老人脚后跟摔了里面有小碎片, 怎么治疗 2 362
妇科 盆腔炎会肚子隐隐痛吗, 没异味, 白带特别粘 4 205
产科 怀孕四个月喝酒抽烟熬夜对胎儿有影响吗 1 937
儿科 7天新生儿综合评分36分踏步反射0分是脑瘫吗 2 294
男科 睾丸紧缩好像变小了, 是怎么回事呢? 2 553
骨伤科 手肘关节处肿胀, 可以不用打石膏固定吗 1 914
营养科 为什么有一种人每天暴饮暴食都不会胖的呢 3 691
肿瘤科 59岁老人宫颈癌放化疗后尿失禁带点血怎么回事 2 103
眼科 62岁青光眼晚期如何治疗 2 822
耳鼻咽喉科 鼻子塞得很严重, 擦了油和通鼻贴完全没有效果, 怎么办 2 036
口腔颌面科 最近这几天刷牙流血越来越厉害了怎么回事 1 926
皮肤性病科 尖锐湿疣有什么特征 1 825
总计 33 073
分类算法 Count TF-IDF
支持向量机 73.4% 75.1%
随机森林 68.6% 70.0%
多项式贝叶斯 71.8% 69.1%
逻辑回归 74.2% 74.0%
k近邻 48.4% 54.9%
集成分类 74.5% 74.4%
科室 数据量 分诊准确率
眼科 565 94.9%
营养科 738 85.0%
口腔颌面科 385 84.2%
耳鼻喉科 407 82.6%
肿瘤科 421 82.2%
妇科 841 82.2%
骨伤科 383 72.6%
内科 681 72.2%
男科 511 72.2%
产科 387 66.1%
儿科 459 64.3%
皮肤性病科 365 62.5%
外科 472 40.9%
原始科室 预测科室 错误率
外科 男科 25%
产科 妇科 22%
儿科 内科 10%
男科 外科 10%
妇科 产科 7%
内科 儿科 6%
骨伤科 皮肤性病科 5%
皮肤性病科 内科 5%
营养科 儿科 5%
肿瘤科 妇科 5%
耳鼻喉科 内科 4%
口腔颌面科 内科 3%
眼科 皮肤性病科 1%
科室 常见高频易混词举例
外科-男科 龟头、阴茎、手淫、勃起、早泄、包皮、尿、睾丸、
疼、精子、性生活、前列腺炎、痒、手术、龟头炎
产科-妇科 月经、怀孕、流产、检查、子宫、出血、严重、疼、
自然流产、分泌物、流血、孩子
儿科-内科 发烧、咳嗽、治疗、感冒、药、反复、症状、大便、
吐、检查、拉肚子、痰
科室 年龄平均值 男性比例 女性比例
妇科 27.2 3.5% 96.5%
产科 27.0 4.1% 95.9%
营养科 23.6 35.1% 64.9%
儿科 10.9 43.1% 56.9%
口腔颌面科 26.6 43.5% 56.5%
皮肤性病科 25.8 44.1% 55.9%
眼科 28.3 45.0% 55.0%
肿瘤科 47.3 45.5% 54.5%
耳鼻喉科 27.8 47.8% 52.2%
内科 34.8 48.9% 51.1%
骨伤科 34.0 51.3% 48.7%
外科 31.3 64.0% 36.0%
男科 26.9 94.4% 5.6%
总体 28.6 43.9% 56.1%
科室 增加特征前准确率 增加特征后准确率 提升率
妇科 82.7% 83.2% 0.5%
产科 67.4% 67.9% 0.5%
营养科 86.7% 87.5% 0.8%
儿科 58.3% 61.8% 3.5%
口腔颌面科 81.6% 82.1% 0.4%
皮肤性病科 60.6% 60.6% 0.0%
眼科 99.4% 99.4% 0.0%
肿瘤科 75.5% 76.6% 1.0%
耳鼻喉科 85.8% 84.7% -1.1%
内科 73.2% 73.8% 0.5%
骨伤科 70.4% 71.1% 0.7%
外科 45.8% 46.4% 0.6%
男科 70.0% 73.5% 3.5%
总体 75.5% 76.3% 0.8%
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