日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer

利用深度学习对常规全乳乳房X光片进行分析,可提高早期乳腺癌淋巴结转移的预测能力

Zhang, Daqu; Dihge, Looket; Bendahl, Pär-Ola; Arvidsson, Ida; Dustler, Magnus; Ellbrant, Julia; Gulis, Kim; Hjärtström, Malin; Ohlsson, Mattias; Rejmer, Cornelia; Schmidt, David; Zackrisson, Sophia; Edén, Patrik; Rydén, Lisa

Development and validation of prediction models for sentinel lymph node status indicating postmastectomy radiotherapy in breast cancer: population-based study

乳腺癌根治术后放疗前哨淋巴结状态预测模型的建立与验证:一项基于人群的研究

Svensson, Miriam; Bendahl, Pär-Ola; Alkner, Sara; Hansson, Emma; Rydén, Lisa; Dihge, Looket

Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis

利用乳腺影像学预测早期乳腺癌患者前哨淋巴结状态(替代手术分期)——系统评价和荟萃分析

Rejmer, Cornelia; Hjärtström, Malin; Bendahl, Pär-Ola; Dihge, Looket; Skarping, Ida; Zhang, Daqu; Dustler, Magnus; Rydén, Lisa

External validation of a multivariable prediction model for positive resection margins in breast-conserving surgery

乳腺癌保乳手术中阳性切缘的多变量预测模型的外部验证

Manhoobi, Irina Palimaru; Ellbrant, Julia; Bendahl, Pär-Ola; Redsted, Søren; Bodilsen, Anne; Tramm, Trine; Christiansen, Peer; Rydén, Lisa

Prediction of High Nodal Burden in Patients With Sentinel Node-Positive Luminal ERBB2-Negative Breast Cancer

预测前哨淋巴结阳性、管腔型、ERBB2阴性乳腺癌患者的高淋巴结负荷

Skarping, Ida; Bendahl, Pär-Ola; Szulkin, Robert; Alkner, Sara; Andersson, Yvette; Bergkvist, Leif; Christiansen, Peer; Filtenborg Tvedskov, Tove; Frisell, Jan; Gentilini, Oreste D; Kontos, Michalis; Kühn, Thorsten; Lundstedt, Dan; Vrou Offersen, Birgitte; Olofsson Bagge, Roger; Reimer, Toralf; Sund, Malin; Rydén, Lisa; de Boniface, Jana

Health-related quality of life by type of breast surgery in women with primary breast cancer: prospective longitudinal cohort study

乳腺癌患者接受不同类型乳腺手术后的健康相关生活质量:前瞻性纵向队列研究

Gulis, Kim; Ellbrant, Julia; Bendahl, Pär-Ola; Svensjö, Tor; Rydén, Lisa

Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750)

回顾性验证基于人工神经网络的乳腺癌原发性患者术前非侵入性淋巴结分期(NILS)决策支持工具(ISRCTN14341750)

Skarping, Ida; Ellbrant, Julia; Dihge, Looket; Ohlsson, Mattias; Huss, Linnea; Bendahl, Pär-Ola; Rydén, Lisa

Preoperative prediction of nodal status using clinical data and artificial intelligence derived mammogram features enabling abstention of sentinel lymph node biopsy in breast cancer

利用临床数据和人工智能衍生的乳腺X线摄影特征进行术前淋巴结状态预测,可避免乳腺癌前哨淋巴结活检。

Rejmer, Cornelia; Dihge, Looket; Bendahl, Pär-Ola; Förnvik, Daniel; Dustler, Magnus; Rydén, Lisa

Model of Health-Related Quality of Life in Breast Cancer Patients Using Cross-Sectional Data: The Role of Resilience

基于横断面数据的乳腺癌患者健康相关生活质量模型:韧性的作用

Velickovic, Katarina; Olsson Möller, Ulrika; Ryden, Lisa; Bendahl, Pär-Ola; Malmström, Marlene

Hormone receptor mRNA and protein levels as predictors of premenopausal tamoxifen benefit

激素受体mRNA和蛋白水平作为预测绝经前他莫昔芬疗效的指标

Engström, Terese; Ekholm, Maria; Fernö, Mårten; Lundgren, Christine; Nordenskjöld, Bo; Stål, Olle; Bendahl, Pär-Ola; Tutzauer, Julia; Rydén, Lisa