Machine learning models based on magnetic resonance imaging for predicting Lymphovascular Invasion in Invasive Breast Cancer.
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| Title: | Machine learning models based on magnetic resonance imaging for predicting Lymphovascular Invasion in Invasive Breast Cancer. |
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| Authors: | Li H; Department of Radiology, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China., Huang J; Department of Radiology, Guangzhou Geriatric Hospital, Guangzhou, Guangdong, China., Hou J; Department of Radiology, Guangzhou Women And Children's Medical Center, Guangzhou, China., Chen X; Department of Breast surgery, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China., Zhi C; Department of Pathology, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China., Li Z; Department of Radiology, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China. |
| Source: | PloS one [PLoS One] 2026 May 29; Vol. 21 (5), pp. e0350085. Date of Electronic Publication: 2026 May 29 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0350085 |
