Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer
Jiang, Meng, Li, Chang-Li, Luo, Xiao-Mao, Chuan, Zhi-Rui, Lv, Wen-Zhi, Li, Xu, Cui, Xin-Wu, Dietrich, Christoph F.·2021·European Journal of Cancer
Cited by (214)
Items 101–200 of 214
- Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancerPu Zhou, Hongyan Qian, Pengfei Zhu, Jiangyuan Ben, Guifang Chen, Qiuyi Chen, Lingli Chen, Jia Chen, Ying He · 2025 · Frontiers in Oncology
- An MRI-based Radiomics Approach to Improve Breast Cancer Histological GradingMeng Di Jiang, Chang-li Li, Xiaomao Luo, Zhi-Rui Chuan, Ruixue Chen, Chao-Ying Jin · 2023 · Academic Radiology
- Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast CancerAilin Lan, Junru Chen, Chao Li, Yudi Jin, Yinan Wu, Yuran Dai, Linshan Jiang, Han Li, Yang Peng, Shengchun Liu · 2023 · International Journal of Environmental Research and Public Health
- Predicting hormone receptor status in invasive breast cancer through radiomics analysis of long-axis and short-axis ultrasound planesJiangfeng Wu, Lifang Ge, Yinghong Guo, Anli Zhao, Jincao Yao, Zhengping Wang, Dong Xu · 2024 · Scientific Reports
- Tumor size, HER-2 status, CA125, CEA, SII, and PNI: key predictors of pathological complete response in LABC patientsXinyi Guo · 2024 · American Journal of Cancer Research
- Integrative multimodal ultrasound and radiomics for early prediction of neoadjuvant therapy response in breast cancer: a clinical studySiyu Wang, Jingyan Liu, Linlin Song, Haina Zhao, Xue Wan, Yulan Peng · 2025 · BMC Cancer
- Unraveling the Pivotal Network of Ultrasound and Somatic Mutations in Triple-Negative and Non-Triple-Negative Breast CancerYunxia Huang, Yi Guo, Qin Xiao, Shuyu Liang, Qiang Yu, Lang Qian, Jin Zhou, Jian Le, Yu‐Chen Pei, Lei Wang et al. · 2023 · Breast Cancer Targets and Therapy
- Ultrasound-Based Radiomics for the Classification of Henoch-Schönlein Purpura Nephritis in ChildrenJie Chen, Zeying Wen, Xiaoqing Yang, Jie Jia, Xiaodong Zhang, Linping Pian, Ping Zhao · 2023 · Ultrasonic Imaging
- The value of machine learning based on magnetic resonance imaging (MRI) and biopsy whole-slide image to predict pathological complete response to breast cancer after neoadjuvant chemotherapy: a two-centre studyJ. Liu, X. Wang, Ning Mao, Hui Hua, X. Zhong, Jiaqi Han, J. Chen · 2025 · Clinical Radiology
- The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysisPeijun Chen, Jiahui Tong, Ting Lin, Ying Wang, Yuehui Yu, Menghan Chen, Gaoyi Yang · 2022 · Gland Surgery
- The Role of Nomogram Based on the Combination of Ultrasound Parameters and Clinical Indicators in the Degree of Pathological Remission of Breast CancerHuangjing Chen, Hongyan Qian, Guifang Chen, Pengfei Zhu, Chunjuan Sun, Xiaotian Wu, Ying He · 2023 · Journal of Oncology
- Deep learning and ultrasound feature fusion model predicts the malignancy of complex cystic and solid breast nodules with color Doppler imagesHan Liu, Chunjie Hou, Jinglan Tang, Li-Tao Sun, Ke‐Feng Lu, Ying Liu, Pei Du · 2023 · Scientific Reports
- Study on the differential diagnosis of benign and malignant breast lesions using a deep learning model based on multimodal imagesYanan Du, Dawei Wang, Menghan Liu, Xiaodong Zhang, Wanqing Ren, Jingxiang Sun, Chao Nan Yin, Shiwei Yang, Li Zhang · 2024 · Journal of Cancer Research and Therapeutics
- Predicting Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic ImagesHikmat Khan, Ziyu Su, Huina Zhang, Yihong Wang, Bohan Ning, Shi Wei, Hua Guo, Zaibo Li, Muhammad Khalid Khan Niazi · 2025 · Cancers
- Comparison of different nutritional screening tools in nutritional screening of patients with cirrhosis: A cross-sectional observational studyRunzhu Wang, Lihua Huang, Min Xu, Yu Xia, Hao Wang · 2024 · Heliyon
- Research on ultrasound-based radiomics: a bibliometric analysisYu Lu, Mengting Che, Xu Wu, Luo Hong · 2024 · Quantitative Imaging in Medicine and Surgery
- CLIP-based multimodal endorectal ultrasound enhances prediction of neoadjuvant chemoradiotherapy response in locally advanced rectal cancerHanchen Zhang, Hang Yi, Si Qin, Xiaoyin Liu, Guangjian Liu · 2024 · PLoS ONE
- The study of ultrasonography based on deep learning in breast cancerYun Peng, Wei Tang, Xiaoyu Peng · 2023 · Journal of Radiation Research and Applied Sciences
- Prediction of heart failure and all-cause mortality using cardiac ultrasomics in patients with breast cancerQuincy Alexander Hathaway, Yahya Abdeen, Justin Conte, Rotem Hass, Matthew J. Santer, Bandar Alyami, Juan Carlo Avalon, Brijesh D. Patel · 2024 · The International Journal of Cardiovascular Imaging
- Development and validation of a multi-modal ultrasomics model to predict response to neoadjuvant chemoradiotherapy in locally advanced rectal cancerQiong Qin, Xiang-Yu Gan, Peng Lin, Jingshu Pang, Ruizhi Gao, Rong Wen, Dun Liu, Quanquan Tang, Changwen Liu, Yun He et al. · 2024 · BMC Medical Imaging
- Deep learning model based on DCE-MRI: fusion of 3D features of tumor, peritumoral vessels and metastatic lymph nodes for prediction of pathological complete response to neoadjuvant therapy in breast cancerYue Du, Yue Zhu, Mengting Yang, Aoqi Zhang, Lei Zhang, Zhihuai Zhou · 2025 · Frontiers in Oncology
- Multi-task learning for joint prediction of breast cancer histological indicators in dynamic contrast-enhanced magnetic resonance imagingRong Sun, Xiujuan Li, Baosan Han, Yuanzhong Xie, Shengdong Nie · 2025 · Computer Methods and Programs in Biomedicine
- Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictorsJiejie Yao, Wei Zhong Zhou, Xiaohong Jia, Ying Zhu, Xiaosong Chen, Weiwei Zhan, Jianqiao Zhou · 2025 · Breast Cancer Research and Treatment
- Multi-modal radiomics model based on four imaging modalities for predicting pathological complete response to neoadjuvant treatment in breast cancerYuwen Liang, Haonan Xu, Jie Lin, Wenqiang Tang, Xinlan Liu, Kunyuan Gan, Qiaodi Wan, Xiaobo Du · 2025 · BMC Cancer
- Ultrasound-based machine learning models for predicting response to neoadjuvant chemotherapy in breast cancer: A meta-analysisParya Valizadeh, Payam Jannatdoust, Niloofar Moradi, Shirin Yaghoobpoor, Sajjad Toofani, Nazanin Rafiei, Farzan Moodi, Hamed Ghorani, Arvin Arian · 2025 · Clinical Imaging
- Longitudinal Ultrasound Delta Radiomics for Early Stratified Prediction of Tumor Response to Neoadjuvant Chemotherapy in Breast CancerMengyun Wang, Zhibin Huang, Hongtian Tian, Sijie Mo, Huaiyu Wu, Jinfeng Xu, Fajin Dong · 2025 · Academic Radiology
- EPD: an integrated modeling technique to classify BCSashikanta Prusty, Sujit Kumar Dash, Srikanta Patnaik, Sushree Gayatri Priyadarsini Prusty, Nrusingha Tripathy · 2023 · International Conference in Advances in Power, Signal, and Information Technology (APSIT)
- Prediction of pathological complete response of breast cancer patients who received neoadjuvant chemotherapy with a nomogram based on clinicopathologic variables, ultrasound, and MRIManqi Zhang, Xinpei Liu, Yu Lei Du, Hailing Zha, Xiaoming Zha, Jue Wang, Xiaoan Liu, Shou-Ju Wang, Qigui Zou, Jiulou Zhang et al. · 2023 · British Journal of Radiology
- Monitoring response to neoadjuvant therapy for breast cancer in all treatment phases using an ultrasound deep learning modelJingwen Zhang, Jingwen Deng, Jin Huang, Liye Mei, Ni Liao, Feng Yao, Cheng Lei, Shengrong Sun, Yimin Zhang · 2024 · Frontiers in Oncology
- Prediction value study of breast cancer tumor infiltrating lymphocyte levels based on ultrasound imaging radiomicsMin Zhang, Xuanyu Li, Pin Zhou, Panpan Zhang, Gang Wang, Xian-fang Lin · 2024 · Frontiers in Oncology
- A ultrasonic nomogram of quantitative parameters for diagnosing breast cancerCong Wang, Ying Che · 2023 · Scientific Reports
- Clinical and radiomics integrated nomogram for preoperative prediction of tumor-infiltrating lymphocytes in patients with triple-negative breast cancerLing Hu, Peile Jin, Wen Xu, Chao Wang, Pintong Huang · 2024 · Frontiers in Oncology
- Ultrasound‐based radiomics‐clinical nomogram for noninvasive prediction of residual cancer burden grading in breast cancerZhiyong Li, Sheng‐Nan Wu, Zhen‐Hu Lin, Meichen Jiang, Cong Chen, Rongxi Liang, Wenjin Lin, Ensheng Xue · 2024 · Journal of Clinical Ultrasound
- A retrospective study on predicting clinically significant prostate cancer via a bi-parametric ultrasound-based deep learning radiomics modelXiang Liu, Zhongxin Zhang, Bing Zheng, Min Xu, Xinyu Cao, Haiming Huang · 2025 · Frontiers in Oncology
- Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models for predicting the pathological differentiation degree in hepatocellular carcinomaKaiying Wu, Zhu Zhu, Dabo Xu, Yujie Lu, Tao Zhang, Ximing Wang, Chunhong Hu, Wenhao Gu, Yixing Yu · 2025 · European Journal of Radiology
- Renal fibrosis assessment in chronic kidney disease: Exploring varied kidney regions with ultrasound-based radiomics analysisZiman Chen, Yingli Wang, Chaoqun Wu · 2025 · Science Progress
- The result prediction of fluorescence in situ hybridization for breast cancer patients based on machine learning and deep learning models: a multicenter studyCong Jiang, Dong Chen, Xiao Yu, Shentao Zhang, Yuting Xiu, Ningbin Luo, Jingjing Wu, XueFang Zhang, Man Chen, Dechun Yang et al. · 2026 · Cancer Imaging
- Ultrasound features combined with tumor-infiltrating lymphocytes for prediction of pathological response to neoadjuvant chemotherapy in breast cancerYingying Jia, Xin Zhou, Yangyang Zhu, Xuewen Song, Ying Duan, Kundi Chen, Fang Nie · 2023 · Medical Ultrasonography
- Deep learning-assisted distinguishing breast phyllodes tumours from fibroadenomas based on ultrasound images: a diagnostic studyYuqi Yan, Yuanzhen Liu, Jincao Yao, Lin Sui, Chen Chen, Tian Jiang, Xiaofang Liu, Yifan Wang, Di Ou, Jing Chen et al. · 2024 · British Journal of Radiology
- CT-based deep learning model for predicting the success of extracorporeal shock wave lithotripsy in treating ureteral stones larger than 1 cmRijin Song, Bo Liu, Huixin Xu · 2024 · Urolithiasis
- Dynamic ultrasound-based modeling predictive of response to neoadjuvant chemotherapy in patients with early breast cancerXinyi Wang, Yuting Zhang, Mengting Yang, Nan Wu, Shan Wang, Hong Chen, Tianyang Zhou, Ying Zhang, Xiaolan Wang, Zining Jin et al. · 2024 · Scientific Reports
- Development of an Ultrasound-Based Radiomics Nomogram for Preoperative Prediction of HER-2 Status in Invasive Breast CancerMaolin Xu, Yulin Liu, Shue Zeng, Fang Li · 2025 · Academic Radiology
- An ultrasound-based model for predicting the response to neoadjuvant chemotherapy in early stage triple negative breast cancer patientsYuyang Tong, Yi Wei, Peixuan Sun, Cai Chang · 2025 · BMC Medical Imaging
- Combining radiomics and deep learning to predict liver metastasis of gastric cancer on CT imageYimin Guo, Haixiang Yin, Hanyue Zhang, Pan Liang, Jianbo Gao, Ming Cheng · 2025 · Frontiers in Oncology
- Ultrasound-based radiomic nomogram for predicting the invasive status of breast cancer: a multicenter studyDan Yan, Jingwen Xie, Wanling Cheng, Xue Wen, Yaohong Den, Jian-xing Zhang · 2025 · European journal of medical research
- Integrating Deep Learning and Radiomics in Differentiating Papillary Thyroid Microcarcinoma from Papillary Thyroid Carcinoma with Ultrasound ImagesBing Yu, Huijuan He, Qiao Zheng, Yao Ai, Xianwen Yu, Sunjun Li, Ji Zhang, Juebin Jin, Xiance Jin, Wenliang Yu · 2025 · Cancer Management and Research
- Integrated conventional ultrasound and radiomics model for predicting major pathological response to neoadjuvant therapy in triple-negative breast cancerRuoxuan Lin, Yijie Chen, Yaoqin Wang, Lina Tang, Weiqin Huang · 2025 · BMC Medical Imaging
- Predicting pathological complete response to breast cancer neoadjuvant therapy using multi-combination machine learning models based on vision transformer featuresLinyong Wu, Songhua Li, Feng Chen, Chaojun Wu, Yan Lin, Shaofeng Wu, Dayou Wei, Xiaohong Xu · 2025 · Scientific Reports
- Improved Fuzzy C-Means Clustering Algorithm-Based Dynamic Contrast-Enhanced Magnetic Resonance Imaging Features in the Diagnosis of Invasive Breast Carcinoma before and after MenopauseMei Li, Kaixiang Wang, GU Yong-jian · 2022 · Computational and Mathematical Methods in Medicine
- Progress in research on ultrasound radiomics for predicting the prognosis of breast cancerXuantong Gong, Xuefeng Liu, Xiaozheng Xie, Yong Wang · 2023 · Cancer Innovation
- Development of an Ultrasound-based Nomogram for Predicting Pathologic Complete Response and Axillary Response in Node-Positive Patients with Triple- Negative Breast CancerManqi Zhang, Hailing Zha, Jiazhen Pan, Xiaoan Liu, Min Zong, Liwen Du, Yu Lei Du · 2024 · Clinical Breast Cancer
- Assessing breast cancer volume alterations post-neoadjuvant chemotherapy through DenseNet-201 deep learning analysis on DCE-MRIZhenqi Gu, Jing Huang, Changyu Zhou, Qi Wang, Jianchun Kong, Xiongbin You, Ziwei Zhang, Hong Zhao · 2024 · Journal of Radiation Research and Applied Sciences
- Nomogram based on multimodal ultrasound features for evaluating breast nonmass lesions: a single center studyLifang Yu, Luo-Xi Zhu, Chaochao Dai, Xiaojing Xu, Yanjuan Tan, Hongju Yan, Lingyun Bao · 2024 · BMC Medical Imaging
- Integration of Longitudinal and Transverse Radiomics from Ultrasound Images with Clinical Factors for HER-2 Status Prediction in Invasive Breast Cancer PatientsJiangfeng Wu, Yinghong Guo, Chao Wu, Zhengping Wang, Yue Sun, Dong Xu · 2024 · Journal of Investigative Surgery
- Artificial intelligence clinical applications in breast diagnostic imagingCalogero Zarcaro, Paola Clauser · 2023 · Journal of Radiological Review
- Value of Molybdenum Target X-Ray and High-Frequency Color Doppler Flow Imaging in Early Diagnosis of Breast Carcinoma: A Comparative AnalysisXia Li, Xu Shuang, Liu-Wei Hao, Xiaoning Zhou · 2023 · Cancer Management and Research
- Noninvasive Assessment of Tumor Histological Grade in Invasive Breast Carcinoma Based on Ultrasound Radiomics and Clinical Characteristics: A Multicenter StudyLifang Ge, Jiangfeng Wu, Yun Jin, Dong Ming Xu, Zhengping Wang · 2024 · Technology in Cancer Research & Treatment
- Correlation and predictive value of pathological complete response and ultrasound characteristic parameters in neoadjuvant chemotherapy for breastLei Zheng, Lixian Yang, Jing-Yi Liu, Zhe Jiang, Xiaowei Li, Pengpeng Pu · 2024 · World Journal of Clinical Cases
- Deep Learning for Distinguishing Mucinous Breast Carcinoma From Fibroadenoma on UltrasoundYuan Yao, Zhao Yang, Xu Guo, Xiangli Xu, Baiyang Fu, Hao Cui, Jian Yang Xue, Jiawei Tian, Ke Lü, Lei Zhang · 2024 · Clinical Breast Cancer
- Advances in radiomics applications for intrahepatic cholangiocarcinoma: a comprehensive review and future directionsJia-Wei Xu, Binghua Li, Decai Yu · 2024 · Hepatoma Research
- Key parameters in intratumoral-peritumoral region fusion models: optimizing deep learning radiomics for breast cancer diagnosisJun-Tao Shen, Gong-Quan Chen, Haimei Lun, Hua-Fang Huang, Ling Zhang, Ling-Ling Li, Yunxia Deng, Hui-Hua Wu, Qiao Hu · 2025 · Frontiers in Oncology
- The utilization of CEUS and SWE for predicting pathological complete response to neoadjuvant chemotherapy for invasive breast cancerYingyan Wang, Xuanli Jiang, Yang Jiao, Bingjie Yang, Pingping Wang, Huiming Shen, Jiajia Xu, Min Qi, Hongyuan Shen, Jiahao Han et al. · 2026 · Scientific Reports
- Radiomics and artificial intelligence for predicting response to neoadjuvant drug therapy in patients with breast cancer: a reviewMaria M. Suleymanova, Grigory Grigorievich Karmazanovsky, Evgeny V. Kondratyev, Anatoly Yu. Popov, Valentin A. Nechaev, M. S. Ermoshchenkova, Evgeniya S. Kuzmina · 2025 · Digital Diagnostics
- Ultrasound-based artificial intelligence for breast lesion classificationTing Ma, Zhen Wang, Jian Dong, Yuhang Cheng, Huan Zhao, Xin Wu Cui · 2026 · Frontiers in Oncology
- Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer using a Longitudinal US-based Stack-modelTian Jiang, Xin Li, Jiafei Shen, Y J Yan, Lin Sui, Lingyan Zhou, Zhiyan Jin, Di Ou, Wang L, Zhirui Chuan et al. · 2026 · Academic Radiology
- Artificial intelligence for predicting pathological complete response to neoadjuvant therapy in triple-negative breast cancer: A systematic review and meta-analysisAndrea Carlini, Flavia Foca, Marianna Sirico, Alberto Farolfi, Chiara Casadei, Caterina Gianni, Michela Palleschi, Nicola Gentili, Marita Mariotti, Giandomenico Di Menna et al. · 2026 · The Breast
- The study of tumor regression mode, Ki67 expression and neoadjuvant chemotherapy on prognosis of different molecular breast cancerXiangjuan Liu, Jun Fang Zhao, Jian Li, Yuan Wang, Hongyan Zang · 2023 · Minerva Surgery
- Development of a deep learning-based automatic detection model for gastroesophageal varices using transient elastographyJian-song Gao, Zixiang Kong, Shu-fang Wei, Fei Liang, Xiaoxiao Chen · 2024 · Journal of Radiation Research and Applied Sciences
- A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer PatientsShuhan Sun, Yajing Chen, Yutong Liu, Cuiying Li, Shumei Miao, Bin Yang, Feihong Yu · 2024 · Academic Radiology
- A deep learning radiomics model based on CT images for predicting the biological activity grading of hepatic cystic echinococcosisMaihemitijiang Damola, Jing Hui Yang, Adilijiang Abulaiti, Aibibulajiang Mutailifu, Diliaremu Aihait, Abudoukeyoumujiang Abulizi, Kahaer Tuerxun, Xiaoguang Zou, Mayidili Nijiati · 2023 · Research Square
- Research Progress of Imaging in Evaluating the Efficacy of Neoadjuvant Therapy for Breast Cancer雅静 周 · 2022 · Advances in Clinical Medicine
- Ultrasound and clinicopathologic feature based model for early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer: A case-control studyTian Jiang, lin sui, yuqi yan, Di Ou, chen chen, chen Ni, Min Lai, Liping Wang, Chen Yang, Wei Li et al. · 2023 · Research Square
- Comparison of different machine learning models based on ultrasound-based radiomics to predict central lymph node metastasis of papillary thyroid carcinomaPeng Zhao, Lulu Liang, Xian Wei, Yongbiao Luo, Quankun Liang, Yulin Bao, Bang‐De Xiang · 2023 · Research Square
- Detection of low expression of molecular subtype HER2 in breast cancer using ultrasound-based radiomicsXueling Zhang, Shaoyou Wu, Xiao Zu, Xiaojing Li, Qing Zhang, Yongzhen Ren, Shan Tong, Hongbo Li · 2023 · Research Square
- Progress on radiomics and radiogenomics and their applications in breast cancer: A survey2023 · Data Science and Informetrics
- Ultrasound-based deep learning radiomics nomogram for comprehensive prediction of tumor, axillary lymph node status and prognosis of breast cancer patients after neoadjuvant chemotherapyYuexia Liu, Qinghua Liu, Quan-Hui Hu, Jiayao Shi, Gui-Lian Liu, Han Liu, Sheng-Chun Shu · 2023 · Research Square
- Improving HER2-Positive Breast Cancer Targeted Therapy Prediction Using multiMSnet: A Multi-Scale Pathological Image-Based ApproachXiaohua Liu, Yi Li, Xiaomin Xiong, Yihan Wu, Mengke Xu, Lin Chen, Lin Bo, Bo Xu, Guoxiang Liu · 2023 · IEEE ... International Conference on Data Mining workshops
- Deep orthogonal multimodality fusion for prediction of axillary lymph node status after neoadjuvant chemotherapyYiliang Li, Jiaxin Huang, Xueyan Wang, Xiao‐Qing Pei, Yao Lu · 2024 · SPIE Medical Imaging: Physics of Medical Imaging
- A Breast Cancer Prognosis Model using PyRadiomics and Image Segmentation from MRI dataMoirangthem Sonia, Indrajit Kalita, Debashree Devi · 2024
- Deep Learning-Enabled Ultrasound Radiomics for Accurate Prediction of Breast Cancer Lymph Node MetastasisMan Wang, Weijia Huang, Erlv Wu, Qishan Cen, Shichun Gao, Zhiyu Li, Dejing Dang, Yanlin Chen, Jiancheng wang, Yeyang Chen et al. · 2024 · Research Square
- Personalized Perioperative Care for a Patient with a 10-Year-Old Postpartum Old Thrombus after Neoadjuvant Therapy for Breast CancerXia Zhang · 2024 · Advances in Breast Cancer Research
- HPN: A Multimodal Neural Network Model for Non-invasive HER2 Status Assessment in Breast Cancer PatientsYuhan Liu, Jinlin Ye, Zecheng He, Mingyue Wang, Changjun Wang, Yidong Zhou, Wei Zhang · 2024 · Research Square
- Evaluating Early Nerve Injury and Its Relationship With Leprosy Reactions in Patients With Leprosy: A Prospective Cohort StudyLan-Mei Lin, Hao Wu, Wan-Rong Zhu, Canbin Dong, Qi Zhang, Cheng-Hui Zheng, Xiaoniu Liang, Heng Long, Jinhua Xu, Hong Ding et al. · 2024 · International Journal of Dermatology and Venereology
- Artificial Intelligence in Breast Imaging: Basic Principles for RadiologistsPratyaksha Rana, Krithika Rangarajan · 2025 · Springer eBooks
- Klinischer Ultraschall Teil II: Sonopsychologie – psychologische Aspekte der Interaktionen im UltraschallClaudia Lucius, Christian Jenssen, Dieter Nürnberg, Daniel Merkel, Dagmar G. Schreiber-Dietrich, E. Merz, Christoph Frank Dietrich · 2025 · Zeitschrift für Gastroenterologie
- The impact of circWWC3 on neoadjuvant therapy for triple-negative breast cancer and the construction of a nomogram for predicting pathological complete response after neoadjuvant therapyHaoqi Wang, Hongbo Liu, Shan Gao, Lijia Wang, Zihao Bai, Yi Zhang, Peijin Zhang, Fei Liu, Cuizhi Geng · 2025 · Frontiers in Oncology
- Research on predicting pathological complete response in breast cancer following neoadjuvant chemotherapy using a multiparametric MRI radiomics modelXinyi Liu, Airu Yang, Mingtai Cao, Qian Zhang, Yuntai Cao · 2025 · Journal of Radiation Research and Applied Sciences
- A Multicenter Study on Formulaic Machine Learning Models for Prediction in Neonatal Necrotizing Enterocolitis: Application and Comparison of Kolmogorov–Arnold NetworksFan He, Jia Wang, Yanbin An, Jinglin Xu, Jiexia Gao, Bowen Weng, Chengyu Wang, Jiahuai Liu, Dongmei Chen, Gaowa Arigong et al. · 2025 · Research Square
- Mammography Based Nomogram Integrating Radiomics and Clinical Features to Predict Benign or Malignant Regression of BI-RADS 4A Lesions at Follow-UpGuoyan Yao, Lijun Chen, Tingfan Wu, Yuanyuan Liu, Yun Wan, Ziqiang Xia, Bo Liu, MinAn Zheng · 2025 · International Journal of Women s Health
- Predictive Analysis of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Using Multi-Region Ultrasound Imaging Features Combined With Pathological ParametersChuanmin Wei, Yingying Jia, Yang Gu, Zhenyu He, Fang Nie · 2025 · Ultrasound in Medicine & Biology
- Development and Validation of Machine Learning Models in Predicting Prognosis of Breast Cancer Patients with Lymph Nodes Metastasis Following Neoadjuvant ChemotherapyYanjia Fan, Yudi Jin, Cheng Tian, Yu Zhang, Chi Zhang, Haochen Yu, Shengchun Liu · 2025 · Breast Cancer Targets and Therapy
- DBT-based habitat imaging for differentiating benign and malignant breast architectural distortion : a two-center studyChong Chen, Kexian Gao, Zhenhui Li, Yingying Ding, Wei Zhao · 2025 · BMC Medical Imaging
- A dual-core driven hybrid radiomics integrates multiple views of greyscale ultrasound image for the early management from diagnosis to biopsy suggestion of BI-RADS 4 breast lesions: a prospective multicenter studyBo Zhou, Liping Sun, Han-Sheng Xia, Bin Tan, Yi-Lei Shi, Hui Liu, Chuan Qin, Yi-Kang Sun, Li-Fan Wang, Xin Guan et al. · 2025 · Cancer Imaging
- Additional file 1 of Development and validation of a radiopathomic model for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer patientsZhang, Jieqiu, Wu, Qi, Wei Yin, Yang, Lu, Xiao, Bo, J.-Z. Wang, Yao, Xiaopeng · 2023 · Figshare
- Additional file 1 of A validation of an entropy-based artificial intelligence for ultrasound data in breast tumorsHuang, Zhibin, Keen Yang, Hongtian Tian, Huaiyu Wu, Tang, Shuzhen, Cui, Chen, Siyuan Shi, Yitao Jiang, Chen, Jing, Xu, Jinfeng et al. · 2024 · Figshare
- Additional file 1 of An integrated deep learning model for the prediction of pathological complete response to neoadjuvant chemotherapy with serial ultrasonography in breast cancer patients: a multicentre, retrospective studyWu, Lei, Ye, Weitao, Liu, Yu, Chen, Dong, Wang, Yuxiang, Cui, Yanfen, Li, Zhenhui, Li, Pinxiong, Li, Zhen, Liu, Zaiyi et al. · 2022 · Figshare
- Additional file 1 of Multiphase and multiparameter MRI-based radiomics for prediction of tumor response to neoadjuvant therapy in locally advanced rectal cancerHuang, Hongyan, 韩路军, Jianbo Guo, Zhang, Yanyu, Lin, Shiwei, Chen, Shengli, Lin, Xiaoshan, Caixue Cheng, Zheng Guo, Qiu, Yingwei · 2023 · Figshare
- A nomogram based on the lymphocyte-to-monocyte ratio and changes in tumor blood supply and volume for predicting pathological complete response of triple negative breast cancer after neoadjuvant chemotherapyTingjian Zhang, Xueyun Zhao, Yuanping Li, Liang Huang, Qiang Zhang, Ying Li, Lingyan Du, Yuyao Liu · 2025 · Research Square
- Breast cancer neoadjuvant chemotherapy treatment response prediction using aligned longitudinal MRI and clinical dataRahul Ravi, Ruizhe Li, Tarek Abdelfatah, Stephen Y.T. Chan, Xin Chen · 2026 · Informatics in Medicine Unlocked
- Dual-Region Ultrasound Radiomics for the Non-Invasive Prediction of HER2 Status in Breast Cancer Patients with Equivocal ImmunohistochemistryX Li, Long Huang, Yu Yan Sun, Chen Yang, Wei Li, Hongping Song, Meiying Yan · 2026 · Research Square