Home ›
Entities
› academia
› Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria
Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria
Research article (PLoS ONE, 2020) · cited 60× · AI/ML
Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria
Summary
Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria is a scholarly article[1].
Key Facts
Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria. Retrieved May 24, 2026, from https://4ort.xyz/entity/detecting-rare-diseases-in-electronic-health-records-using-machine-learning-and-knowledge-engineering-case-study-of-acut
MLA“Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/detecting-rare-diseases-in-electronic-health-records-using-machine-learning-and-knowledge-engineering-case-study-of-acut.
BibTeX@misc{4ortxyz_detecting-rare-diseases-in-electronic-health-records-using-machine-learning-and-knowledge-engineering-case-study-of-acut_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria}}, year = {2026}, url = {https://4ort.xyz/entity/detecting-rare-diseases-in-electronic-health-records-using-machine-learning-and-knowledge-engineering-case-study-of-acut}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria — https://4ort.xyz/entity/detecting-rare-diseases-in-electronic-health-records-using-machine-learning-and-knowledge-engineering-case-study-of-acut (retrieved 2026-05-24)