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

MRI-based digital twins to improve treatment response of breast cancer by optimizing neoadjuvant chemotherapy regimens

利用基于磁共振成像的数字孪生技术优化新辅助化疗方案，以提高乳腺癌的治疗反应

期刊:npj Digital Medicine
影响因子:15.1
doi:10.1038/s41746-025-01579-1
Wu, Chengyue; Lima, Ernesto A B F; Stowers, Casey E; Xu, Zhan; Yam, Clinton; Son, Jong Bum; Ma, Jingfei; Rauch, Gaiane M; Yankeelov, Thomas E
肿瘤
肿瘤免疫
乳腺癌
发表日期：2025
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Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer

结合生物学和MRI数据驱动建模预测三阴性乳腺癌患者对新辅助化疗的反应

期刊:Radiology-Artificial Intelligence
影响因子:13.2
doi:10.1148/ryai.240124
Stowers, Casey E; Wu, Chengyue; Xu, Zhan; Kumar, Sidharth; Yam, Clinton; Son, Jong Bum; Ma, Jingfei; Tamir, Jonathan I; Rauch, Gaiane M; Yankeelov, Thomas E
肿瘤
肿瘤免疫
乳腺癌
发表日期：2025
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Forecasting Chemoradiation Response Midtreatment for High-Grade Gliomas Through Patient-Specific Biology-Based Modeling

基于患者特异性生物学模型预测高级别胶质瘤化疗放疗中期反应

期刊:International Journal of Radiation Oncology Biology Physics
影响因子:6.5
doi:10.1016/j.ijrobp.2025.07.1423
Hormuth, David A 2nd; Farhat, Maguy; Panthi, Bikash; Langshaw, Holly; Shanker, Mihir D; Talpur, Wasif; Thrower, Sara; Goldman, Jodi; Ty, Sophia; Custer, Calliope; Kowalski, Jeanne; Yankeelov, Thomas E; Chung, Caroline
胶质瘤
发表日期：2025
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Investigating the Limits of Predictability of Magnetic Resonance Imaging-Based Mathematical Models of Tumor Growth

探究基于磁共振成像的肿瘤生长数学模型的预测能力极限

期刊:Cancers
影响因子:4.4
doi:10.3390/cancers17203361
LaMonica, Megan F; Yankeelov, Thomas E; Hormuth, David A 2nd
肿瘤
肿瘤免疫
发表日期：2025
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Predicting the response of triple negative breast cancer to neoadjuvant systemic therapy via biology-based modeling and habitat analysis

通过基于生物学的建模和栖息地分析预测三阴性乳腺癌对新辅助全身治疗的反应

期刊:Scientific Reports
影响因子:3.9
doi:10.1038/s41598-025-25989-z
Stowers, Casey E; Wu, Chengyue; Yam, Clinton; Ma, Jingfei; Rauch, Gaiane M; Yankeelov, Thomas E
肿瘤
肿瘤免疫
乳腺癌
发表日期：2025
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Personalizing neoadjuvant chemotherapy regimens for triple-negative breast cancer using a biology-based digital twin

利用基于生物学的数字孪生技术，为三阴性乳腺癌患者制定个性化的新辅助化疗方案。

期刊:npj Systems Biology and Applications
影响因子:3.5
doi:10.1038/s41540-025-00531-z
Christenson, Chase; Wu, Chengyue; Hormuth, David A 2nd; Ma, Jingfei; Yam, Clinton; Rauch, Gaiane M; Yankeelov, Thomas E
肿瘤
肿瘤免疫
乳腺癌
发表日期：2025
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Modeling tumor dynamics and predicting response to therapies in a murine pancreatic cancer model

在小鼠胰腺癌模型中模拟肿瘤动力学并预测治疗反应

期刊:npj Systems Biology and Applications
影响因子:3.5
doi:10.1038/s41540-025-00593-z
Vishwanath, Krithik; Choi, Hoon; Gupta, Mamta; Zhou, Rong; Sorace, Anna G; Yankeelov, Thomas E; Lima, Ernesto A B F
胰腺癌
肿瘤
肿瘤免疫
发表日期：2025
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A data assimilation framework for predicting the spatiotemporal response of high-grade gliomas to chemoradiation

用于预测高级别胶质瘤对放化疗时空响应的数据同化框架

期刊:BMC Cancer
影响因子:3.4
doi:10.1186/s12885-025-14557-3
Miniere, Hugo J M; Hormuth, David A 2nd; Lima, Ernesto A B F; Farhat, Maguy; Panthi, Bikash; Langshaw, Holly; Shanker, Mihir D; Talpur, Wasif; Thrower, Sara; Goldman, Jodi; Ty, Sophia; Chung, Caroline; Yankeelov, Thomas E
胶质瘤
发表日期：2025
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Modeling tumor dynamics and predicting response to chemo-, targeted-, and immune-therapies in a murine model of pancreatic cancer

在小鼠胰腺癌模型中模拟肿瘤动力学并预测对化疗、靶向治疗和免疫疗法的反应

期刊:
影响因子:
doi:10.1101/2025.01.03.631015
Vishwanath, Krithik; Choi, Hoon; Gupta, Mamta; Zhou, Rong; Sorace, Anna G; Yankeelov, Thomas E; Lima, Ernesto A B F
胰腺癌
肿瘤
肿瘤免疫
免疫/内分泌
发表日期：2025
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A critical assessment of artificial intelligence in magnetic resonance imaging of cancer

对人工智能在癌症磁共振成像中的应用进行批判性评估

期刊:
影响因子:
doi:10.1038/s44303-025-00076-0
Wu, Chengyue; Andaloussi, Meryem Abbad; Hormuth, David A 2nd; Lima, Ernesto A B F; Lorenzo, Guillermo; Stowers, Casey E; Ravula, Sriram; Levac, Brett; Dimakis, Alexandros G; Tamir, Jonathan I; Brock, Kristy K; Chung, Caroline; Yankeelov, Thomas E
肿瘤
肿瘤免疫
发表日期：2025
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