Transvaginal ultrasound-based radiomics and integrated clinical indicators via multimodal deep learning for prediction of endometrial polyp recurrence after hysteroscopic surgery.
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| Title: | Transvaginal ultrasound-based radiomics and integrated clinical indicators via multimodal deep learning for prediction of endometrial polyp recurrence after hysteroscopic surgery. |
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| Authors: | Shen Y; Department of Gynecology, Hefei First People's Hospital (Binhu Branch), Hefei, China., Ding B; Department of Gynecology, Hefei First People's Hospital (Binhu Branch), Hefei, China., Li J; Department of Gynecology, Hefei First People's Hospital (Binhu Branch), Hefei, China. |
| Source: | Biomedizinische Technik. Biomedical engineering [Biomed Tech (Berl)] 2026 Jun 26. Date of Electronic Publication: 2026 Jun 26. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Walter de Gruyter Publishers Country of Publication: Germany NLM ID: 1262533 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1862-278X (Electronic) Linking ISSN: 00135585 NLM ISO Abbreviation: Biomed Tech (Berl) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1862-278X |
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| DOI: | 10.1515/bmt-2026-0223 |
