Home ›
Entities
› academia
› Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma
Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma
Research article (Journal of Cancer, 2018) · cited 84× · AI/ML
Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma
Summary
Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma is a scholarly article[1].
Key Facts
Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma'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). Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma. Retrieved May 24, 2026, from https://4ort.xyz/entity/adrenal-incidentaloma-machine-learning-based-quantitative-texture-analysis-of-unenhanced-ct-can-effectively-differentiat
MLA“Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/adrenal-incidentaloma-machine-learning-based-quantitative-texture-analysis-of-unenhanced-ct-can-effectively-differentiat.
BibTeX@misc{4ortxyz_adrenal-incidentaloma-machine-learning-based-quantitative-texture-analysis-of-unenhanced-ct-can-effectively-differentiat_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma}}, year = {2026}, url = {https://4ort.xyz/entity/adrenal-incidentaloma-machine-learning-based-quantitative-texture-analysis-of-unenhanced-ct-can-effectively-differentiat}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma — https://4ort.xyz/entity/adrenal-incidentaloma-machine-learning-based-quantitative-texture-analysis-of-unenhanced-ct-can-effectively-differentiat (retrieved 2026-05-24)