FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3132834592> ?p ?o ?g. }

• W3132834592 endingPage "105" @default.
• W3132834592 startingPage "95" @default.
• W3132834592 abstract "Purpose The aim of the study was to develop and validate a deep learning radiomic nomogram (DLRN) for preoperatively assessing breast cancer pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) based on the pre- and post-treatment ultrasound. Methods Patients with locally advanced breast cancer (LABC) proved by biopsy who proceeded to undergo preoperative NAC were enrolled from hospital #1 (training cohort, 356 cases) and hospital #2 (independent external validation cohort, 236 cases). Deep learning and handcrafted radiomic features reflecting the phenotypes of the pre-treatment (radiomic signature [RS] 1) and post-treatment tumour (RS2) were extracted. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator regression were used for feature selection and RS construction. A DLRN was then developed based on the RSs and independent clinicopathological risk factors. The performance of the model was assessed with regard to calibration, discrimination and clinical usefulness. Results The DLRN predicted the pCR status with accuracy, yielded an area under the receiver operator characteristic curve of 0.94 (95% confidence interval, 0.91–0.97) in the validation cohort, with good calibration. The DLRN outperformed the clinical model and single RS within both cohorts (P < 0.05, as per the DeLong test) and performed better than two experts' prediction of pCR (both P < 0.01 for comparison of total accuracy). Besides, prediction within the hormone receptor–positive/human epidermal growth factor receptor 2 (HER2)–negative, HER2+ and triple-negative subgroups also achieved good discrimination performance, with an AUC of 0.90, 0.95 and 0.93, respectively, in the external validation cohort. Decision curve analysis confirmed that the model was clinically useful. Conclusion A deep learning–based radiomic nomogram had good predictive value for pCR in LABC, which could provide valuable information for individual treatment." @default.
• W3132834592 created "2021-03-01" @default.
• W3132834592 creator A5029416228 @default.
• W3132834592 creator A5030008782 @default.
• W3132834592 creator A5034913846 @default.
• W3132834592 creator A5046527141 @default.
• W3132834592 creator A5052279820 @default.
• W3132834592 creator A5053550143 @default.
• W3132834592 creator A5076557284 @default.
• W3132834592 creator A5089857384 @default.
• W3132834592 date "2021-04-01" @default.
• W3132834592 modified "2023-10-09" @default.
• W3132834592 title "Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer" @default.
• W3132834592 cites W2007463346 @default.
• W3132834592 cites W2011241834 @default.
• W3132834592 cites W2046861708 @default.
• W3132834592 cites W2053074390 @default.
• W3132834592 cites W2071197092 @default.
• W3132834592 cites W2075894019 @default.
• W3132834592 cites W2087179076 @default.
• W3132834592 cites W2295340876 @default.
• W3132834592 cites W2517065464 @default.
• W3132834592 cites W2547978054 @default.
• W3132834592 cites W2726440677 @default.
• W3132834592 cites W2738090720 @default.
• W3132834592 cites W2766525994 @default.
• W3132834592 cites W2767128594 @default.
• W3132834592 cites W2771390751 @default.
• W3132834592 cites W2790518791 @default.
• W3132834592 cites W2806209829 @default.
• W3132834592 cites W2896084151 @default.
• W3132834592 cites W2896886167 @default.
• W3132834592 cites W2916703039 @default.
• W3132834592 cites W2921520311 @default.
• W3132834592 cites W2924275361 @default.
• W3132834592 cites W2926614757 @default.
• W3132834592 cites W2939014135 @default.
• W3132834592 cites W2939853793 @default.
• W3132834592 cites W2979075557 @default.
• W3132834592 cites W2999400187 @default.
• W3132834592 cites W3002866765 @default.
• W3132834592 cites W3005362957 @default.
• W3132834592 doi "https://doi.org/10.1016/j.ejca.2021.01.028" @default.
• W3132834592 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33639324" @default.
• W3132834592 hasPublicationYear "2021" @default.
• W3132834592 type Work @default.
• W3132834592 sameAs 3132834592 @default.
• W3132834592 citedByCount "65" @default.
• W3132834592 countsByYear W31328345922021 @default.
• W3132834592 countsByYear W31328345922022 @default.
• W3132834592 countsByYear W31328345922023 @default.
• W3132834592 crossrefType "journal-article" @default.
• W3132834592 hasAuthorship W3132834592A5029416228 @default.
• W3132834592 hasAuthorship W3132834592A5030008782 @default.
• W3132834592 hasAuthorship W3132834592A5034913846 @default.
• W3132834592 hasAuthorship W3132834592A5046527141 @default.
• W3132834592 hasAuthorship W3132834592A5052279820 @default.
• W3132834592 hasAuthorship W3132834592A5053550143 @default.
• W3132834592 hasAuthorship W3132834592A5076557284 @default.
• W3132834592 hasAuthorship W3132834592A5089857384 @default.
• W3132834592 hasConcept C121608353 @default.
• W3132834592 hasConcept C126322002 @default.
• W3132834592 hasConcept C126838900 @default.
• W3132834592 hasConcept C143998085 @default.
• W3132834592 hasConcept C207886595 @default.
• W3132834592 hasConcept C2778292576 @default.
• W3132834592 hasConcept C34626388 @default.
• W3132834592 hasConcept C44249647 @default.
• W3132834592 hasConcept C530470458 @default.
• W3132834592 hasConcept C58471807 @default.
• W3132834592 hasConcept C71924100 @default.
• W3132834592 hasConcept C72563966 @default.
• W3132834592 hasConceptScore W3132834592C121608353 @default.
• W3132834592 hasConceptScore W3132834592C126322002 @default.
• W3132834592 hasConceptScore W3132834592C126838900 @default.
• W3132834592 hasConceptScore W3132834592C143998085 @default.
• W3132834592 hasConceptScore W3132834592C207886595 @default.
• W3132834592 hasConceptScore W3132834592C2778292576 @default.
• W3132834592 hasConceptScore W3132834592C34626388 @default.
• W3132834592 hasConceptScore W3132834592C44249647 @default.
• W3132834592 hasConceptScore W3132834592C530470458 @default.
• W3132834592 hasConceptScore W3132834592C58471807 @default.
• W3132834592 hasConceptScore W3132834592C71924100 @default.
• W3132834592 hasConceptScore W3132834592C72563966 @default.
• W3132834592 hasLocation W31328345921 @default.
• W3132834592 hasOpenAccess W3132834592 @default.
• W3132834592 hasPrimaryLocation W31328345921 @default.
• W3132834592 hasRelatedWork W2063981093 @default.
• W3132834592 hasRelatedWork W2133675782 @default.
• W3132834592 hasRelatedWork W2295951098 @default.
• W3132834592 hasRelatedWork W3097058703 @default.
• W3132834592 hasRelatedWork W3168769515 @default.
• W3132834592 hasRelatedWork W3208351334 @default.
• W3132834592 hasRelatedWork W3216330551 @default.
• W3132834592 hasRelatedWork W4292307375 @default.
• W3132834592 hasRelatedWork W4324339502 @default.
• W3132834592 hasRelatedWork W4362730554 @default.
• W3132834592 hasVolume "147" @default.

• next