DEKGB: An Extensible Framework for Health Knowledge Graph

2019 ◽  
pp. 27-38 ◽  
Author(s):  
Ming Sheng ◽  
Yuyao Shao ◽  
Yong Zhang ◽  
Chao Li ◽  
Chunxiao Xing ◽  
...  
Keyword(s):  
Health Knowledge ◽  
Knowledge Graph

scholarly journals Mining health knowledge graph for health risk prediction

2020 ◽  
Vol 23 (4) ◽  
pp. 2341-2362 ◽  
Author(s):  
Xiaohui Tao ◽  
Thuan Pham ◽  
Ji Zhang ◽  
Jianming Yong ◽  
Wee Pheng Goh ◽  
...  
Keyword(s):  
Health Risk ◽  
Risk Prediction ◽  
Health Knowledge ◽  
Knowledge Graph

scholarly journals Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph

2019 ◽  
Author(s):  
Irene Y. Chen ◽  
Monica Agrawal ◽  
Steven Horng ◽  
David Sontag
Keyword(s):  
Health Knowledge ◽  
Medical Knowledge ◽  
Knowledge Graph

Doctor recommendation on healthcare consultation platforms: an integrated framework of knowledge graph and deep learning

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hui Yuan ◽  
Weiwei Deng
Keyword(s):  
Deep Learning ◽  
Health Knowledge ◽  
Information Overload ◽  
Knowledge Graph ◽  
Data Sparsity ◽  
Content Type ◽  
Learning Techniques ◽  
Doctor Recommendation ◽  
Managerial Implications ◽  
Sparsity Problem

PurposeRecommending suitable doctors to patients on healthcare consultation platforms is important to both the patients and the platforms. Although doctor recommendation methods have been proposed, they failed to explain recommendations and address the data sparsity problem, i.e. most patients on the platforms are new and provide little information except disease descriptions. This research aims to develop an interpretable doctor recommendation method based on knowledge graph and interpretable deep learning techniques to fill the research gaps.Design/methodology/approachThis research proposes an advanced doctor recommendation method that leverages a health knowledge graph to overcome the data sparsity problem and uses deep learning techniques to generate accurate and interpretable recommendations. The proposed method extracts interactive features from the knowledge graph to indicate implicit interactions between patients and doctors and identifies individual features that signal the doctors' service quality. Then, the authors feed the features into a deep neural network with layer-wise relevance propagation to generate readily usable and interpretable recommendation results.FindingsThe proposed method produces more accurate recommendations than diverse baseline methods and can provide interpretations for the recommendations.Originality/valueThis study proposes a novel doctor recommendation method. Experimental results demonstrate the effectiveness and robustness of the method in generating accurate and interpretable recommendations. The research provides a practical solution and some managerial implications to online platforms that confront information overload and transparency issues.

scholarly journals Learning a Health Knowledge Graph from Electronic Medical Records

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Maya Rotmensch ◽  
Yoni Halpern ◽  
Abdulhakim Tlimat ◽  
Steven Horng ◽  
David Sontag
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Health Knowledge ◽  
Knowledge Graph

The Effects of Domain General and Health Knowledge on Reading General and Health Texts among Older Adults with Hypertension

2011 ◽  
Author(s):  
Jessie Chin ◽  
Daniel G. Morrow ◽  
Elizabeth A. L. Stine-Morrow ◽  
Xuefei Gao ◽  
Thembi Conner-Garcia ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Knowledge

The Effects of Domain General and Health Knowledge in Processing General and Health Texts among Older Adults with Hypertension

2011 ◽  
Author(s):  
Jessie Chin ◽  
Elizabeth A. L. Stine-Morrow ◽  
Dan Morrow ◽  
Xuefei Gao ◽  
Thembi Conner-Garcia ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Knowledge

Perceived Versus Actual Health Knowledge in Undergraduates

2006 ◽  
Author(s):  
Kelly Orourke ◽  
Christy Zenner ◽  
Mary Pritchard
Keyword(s):  
Health Knowledge ◽  
Actual Health

Medical Student Sexual Health Knowledge Survey

2018 ◽  
Author(s):  
Christina Warner ◽  
Samantha Carlson ◽  
Renee Crichlow ◽  
Michael W. Ross
Keyword(s):  
Medical Student ◽  
Sexual Health ◽  
Health Knowledge ◽  
Knowledge Survey ◽  
Sexual Health Knowledge
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