Home ›
Entities
› academia
› Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms
Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms
Research article (International Journal of Medical Informatics, 2020) · cited 44× · AI/ML
Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms
Summary
Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms is a scholarly article[1].
Key Facts
Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms'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). Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-the-hotspots-of-age-adjusted-mortality-rates-of-lower-respiratory-infection-across-the-continental-united-sta
MLA“Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-the-hotspots-of-age-adjusted-mortality-rates-of-lower-respiratory-infection-across-the-continental-united-sta.
BibTeX@misc{4ortxyz_predicting-the-hotspots-of-age-adjusted-mortality-rates-of-lower-respiratory-infection-across-the-continental-united-sta_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-the-hotspots-of-age-adjusted-mortality-rates-of-lower-respiratory-infection-across-the-continental-united-sta}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms — https://4ort.xyz/entity/predicting-the-hotspots-of-age-adjusted-mortality-rates-of-lower-respiratory-infection-across-the-continental-united-sta (retrieved 2026-05-24)
