日期 影响因子
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

期刊:npj Digital Medicine
影响因子:15.1
doi:10.1038/s41746-025-01831-8
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
肿瘤
肿瘤免疫
乳腺癌
发表日期：2025
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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

期刊:BJS Open
影响因子:4.5
doi:10.1093/bjsopen/zraf047
Svensson, Miriam; Bendahl, Pär-Ola; Alkner, Sara; Hansson, Emma; Rydén, Lisa; Dihge, Looket
肿瘤
肿瘤免疫
乳腺癌
发表日期：2025
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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

期刊:Systematic Reviews
影响因子:3.9
doi:10.1186/s13643-025-03005-9
Rejmer, Cornelia; Hjärtström, Malin; Bendahl, Pär-Ola; Dihge, Looket; Skarping, Ida; Zhang, Daqu; Dustler, Magnus; Rydén, Lisa
肿瘤免疫
肿瘤
乳腺癌
发表日期：2025
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Impact of type 2 diabetes on complications after primary breast cancer surgery: Danish population-based cohort study

2型糖尿病对原发性乳腺癌手术后并发症的影响：丹麦人群队列研究

期刊:British Journal of Surgery
影响因子:8.8
doi:10.1093/bjs/znae072
Kjærgaard, Kasper; Wheler, Jannik; Dihge, Looket; Christiansen, Peer; Borgquist, Signe; Cronin-Fenton, Deirdre
肿瘤
肿瘤免疫
乳腺癌
代谢
糖尿病
发表日期：2024
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Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics

基于临床病理特征的深度学习方法识别乳腺癌前哨淋巴结大转移

期刊:Scientific Reports
影响因子:3.9
doi:10.1038/s41598-024-78040-y
Zhang, Daqu; Svensson, Miriam; Edén, Patrik; Dihge, Looket
肿瘤
肿瘤免疫
乳腺癌
发表日期：2024
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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）

期刊:BMC Cancer
影响因子:3.4
doi:10.1186/s12885-024-11854-1
Skarping, Ida; Ellbrant, Julia; Dihge, Looket; Ohlsson, Mattias; Huss, Linnea; Bendahl, Pär-Ola; Rydén, Lisa
肿瘤
SRC
乳腺癌
肿瘤免疫
发表日期：2024
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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。

期刊:Frontiers in Oncology
影响因子:3.3
doi:10.3389/fonc.2024.1394448
Rejmer, Cornelia; Dihge, Looket; Bendahl, Pär-Ola; Förnvik, Daniel; Dustler, Magnus; Rydén, Lisa
肿瘤
肿瘤免疫
乳腺癌
发表日期：2024
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The implementation of NILS: A web-based artificial neural network decision support tool for noninvasive lymph node staging in breast cancer

NILS的实施：一种基于网络的用于乳腺癌非侵入性淋巴结分期的神经网络决策支持工具

期刊:Frontiers in Oncology
影响因子:3.3
doi:10.3389/fonc.2023.1102254
Dihge, Looket; Bendahl, Pär-Ola; Skarping, Ida; Hjärtström, Malin; Ohlsson, Mattias; Rydén, Lisa
肿瘤
肿瘤免疫
乳腺癌
发表日期：2023
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Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development

利用机器学习对乳腺癌淋巴结状态进行无创分期：外部验证和模型进一步开发

期刊:JMIR Cancer
影响因子:2.7
doi:10.2196/46474
Hjärtström, Malin; Dihge, Looket; Bendahl, Pär-Ola; Skarping, Ida; Ellbrant, Julia; Ohlsson, Mattias; Rydén, Lisa
肿瘤
肿瘤免疫
乳腺癌
发表日期：2023
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The implementation of a noninvasive lymph node staging (NILS) preoperative prediction model is cost effective in primary breast cancer

在原发性乳腺癌中，实施非侵入性淋巴结分期（NILS）术前预测模型具有成本效益。

期刊:Breast Cancer Research and Treatment
影响因子:3
doi:10.1007/s10549-022-06636-x
Skarping, Ida; Nilsson, Kristoffer; Dihge, Looket; Fridhammar, Adam; Ohlsson, Mattias; Huss, Linnea; Bendahl, Pär-Ola; Steen Carlsson, Katarina; Rydén, Lisa
肿瘤
肿瘤免疫
乳腺癌
发表日期：2022
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