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IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine
Research article (Neurocomputing, 2019) · cited 13× · AI/ML
IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine
Summary
IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine is a scholarly article[1].
Key Facts
IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine. Retrieved May 24, 2026, from https://4ort.xyz/entity/ihpreten-a-novel-supervised-learning-framework-with-attribute-regularization-for-prediction-of-incompatible-herb-pair-in
MLA“IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/ihpreten-a-novel-supervised-learning-framework-with-attribute-regularization-for-prediction-of-incompatible-herb-pair-in.
BibTeX@misc{4ortxyz_ihpreten-a-novel-supervised-learning-framework-with-attribute-regularization-for-prediction-of-incompatible-herb-pair-in_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine}}, year = {2026}, url = {https://4ort.xyz/entity/ihpreten-a-novel-supervised-learning-framework-with-attribute-regularization-for-prediction-of-incompatible-herb-pair-in}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): IHPreten: A novel supervised learning framework with attribute regularization for prediction of incompatible herb pair in traditional Chinese medicine — https://4ort.xyz/entity/ihpreten-a-novel-supervised-learning-framework-with-attribute-regularization-for-prediction-of-incompatible-herb-pair-in (retrieved 2026-05-24)
