Home ›
Entities
› academia
› Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies
Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies
Research article (Computers in Biology and Medicine, 2022) · cited 49× · AI/ML
Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies
Summary
Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies is a scholarly article[1].
Key Facts
Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies'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 breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-breast-cancer-recurrence-and-metastasis-risk-by-integrating-color-and-texture-features-of-histopathological-i
MLA“Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-breast-cancer-recurrence-and-metastasis-risk-by-integrating-color-and-texture-features-of-histopathological-i.
BibTeX@misc{4ortxyz_predicting-breast-cancer-recurrence-and-metastasis-risk-by-integrating-color-and-texture-features-of-histopathological-i_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-breast-cancer-recurrence-and-metastasis-risk-by-integrating-color-and-texture-features-of-histopathological-i}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting breast cancer recurrence and metastasis risk by integrating color and texture features of histopathological images and machine learning technologies — https://4ort.xyz/entity/predicting-breast-cancer-recurrence-and-metastasis-risk-by-integrating-color-and-texture-features-of-histopathological-i (retrieved 2026-05-24)
