首页|Findings from Northeastern University Update Knowledge of Computational Intellig ence (Multi-hop Reasoning With Relation Based Node Quality Evaluation for Sparse Medical Knowledge Graph)
Findings from Northeastern University Update Knowledge of Computational Intellig ence (Multi-hop Reasoning With Relation Based Node Quality Evaluation for Sparse Medical Knowledge Graph)
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Data detailed on Machine Learning-Co mputational Intelligence have been presented. According to news reporting origin ating in Shenyang, People's Republic of China, by NewsRx journalists, research s tated, "Medical knowledge graph (KG) is sparse KG that contains insufficient inf ormation and missing paths. Multi-hop reasoning is an effective approach of medi cal KG completion, since it offers logical insights of the underlying KG and sho ws more direct interpretability." Financial supporters for this research include Guangdong Basic and Applied Basic Research Foundation, Key Technologies R&D Program of Liaoning Prov ince, Key Project of Science and Technology Innovation and Entrepreneurship of T DTEC.
ShenyangPeople's Republic of ChinaAsiaComputational IntelligenceMachine LearningNortheastern University
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