Arefan相关文献与解析，生知库 | 链接生命科学的每一步

Machine learning to identify hypoxic-ischemic brain injury on early head CT after pediatric cardiac arrest

利用机器学习技术识别儿童心脏骤停后早期头部CT扫描中的缺氧缺血性脑损伤

doi:10.1016/j.resuscitation.2025.110693

Kirschen, Matthew P; Li, Jiren; Elmer, Jonathan; Manteghinejad, Amirreza; Arefan, Dooman; Graham, Kathryn; Morgan, Ryan W; Nadkarni, Vinay; Diaz-Arrastia, Ramon; Berg, Robert; Topjian, Alexis; Vossough, Arastoo; Wu, Shandong

神经科学

发表日期：2025

文献求助收藏

Safe Breast Cancer Diagnosis Resilient to Mammographic Adversarial Samples

安全可靠的乳腺癌诊断方法，不受乳腺X线摄影对抗样本的影响

期刊:

影响因子:

doi:10.1007/978-3-031-77789-9_23

Hao, Degan; Arefan, Dooman; Zuley, Margarita L; Berg, Wendie A; Wu, Shandong

Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk

动态增强磁共振成像中背景实质增强的评估在预测乳腺癌复发风险中的作用

期刊:Radiology

影响因子:15.2

doi:10.1148/radiol.230269

Arefan, Dooman; Zuley, Margarita L; Berg, Wendie A; Yang, Lu; Sumkin, Jules H; Wu, Shandong

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study

利用深度学习技术对乳腺X光图像进行分析，以减少不必要的乳腺活检：一项初步研究

期刊:Breast Cancer Research

影响因子:5.6

doi:10.1186/s13058-024-01830-9

Liu, Chang; Sun, Min; Arefan, Dooman; Zuley, Margarita; Sumkin, Jules; Wu, Shandong

发表日期：2024

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A CT-based radiomics model for predicting renal capsule invasion in renal cell carcinoma

基于CT的放射组学模型预测肾细胞癌肾包膜侵犯

期刊:BMC Medical Imaging

影响因子:3.2

doi:10.1186/s12880-022-00741-5

Yang, Lu; Gao, Long; Arefan, Dooman; Tan, Yuchuan; Dan, Hanli; Zhang, Jiuquan

Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes

基于放射影像表型预测乳腺肿瘤微环境中的细胞侵袭

期刊:BMC Cancer

影响因子:3.4

doi:10.1186/s12885-021-08122-x

Arefan, Dooman; Hausler, Ryan M; Sumkin, Jules H; Sun, Min; Wu, Shandong

Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics

利用多参数肝脏MRI放射组学进行术前微血管侵犯预测

期刊:Journal of Digital Imaging

影响因子:3.8

doi:10.1007/s10278-020-00353-x

Nebbia, Giacomo; Zhang, Qian; Arefan, Dooman; Zhao, Xinxiang; Wu, Shandong

发表日期：2020

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MS-2 Minimally invasive glioma surgery with navigation system and tubular retractor

MS-2 微创胶质瘤手术，配备导航系统和管状牵开器

期刊:Electronic Physician

影响因子:

doi:10.19082/2726

Abdolmohammadi, Jamil; Shafiee, Mohsen; Faeghi, Fariborz; Arefan, Douman; Zali, Alireza; Motiei-Langroudi, Rouzbeh; Farshidfar, Zahra; Nazarlou, Ali Kiani; Tavakkoli, Ali; Yarham, Mohammad; Kurozumi, Kazuhiko

The Role of Single Voxel MR Spectroscopy, T2 Relaxation Time and Apparent Diffusion Coefficient in Determining the Cellularity of Brain Tumors by MATLAB Software

利用MATLAB软件分析单体素磁共振波谱、T2弛豫时间和表观扩散系数在确定脑肿瘤细胞密度中的作用

期刊:Asian Pacific Journal of Cancer Prevention

影响因子:

doi:10.22034/APJCP.2018.19.10.2891

Abdolmohammadi, Jamil; Faeghi, Fariborz; Arefan, Douman; Zali, Alireza; Haghighatkhah, Hamidreza; Amiri, Jamal

Δt -Mamba3D: A Time-Aware Spatio-Temporal State-Space Model for Breast Cancer Risk Prediction

Δt-Mamba3D：一种用于乳腺癌风险预测的时间感知时空状态空间模型

Machine learning to identify hypoxic-ischemic brain injury on early head CT after pediatric cardiac arrest

利用机器学习技术识别儿童心脏骤停后早期头部CT扫描中的缺氧缺血性脑损伤

Safe Breast Cancer Diagnosis Resilient to Mammographic Adversarial Samples

安全可靠的乳腺癌诊断方法，不受乳腺X线摄影对抗样本的影响

Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk

动态增强磁共振成像中背景实质增强的评估在预测乳腺癌复发风险中的作用

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study

利用深度学习技术对乳腺X光图像进行分析，以减少不必要的乳腺活检：一项初步研究

A CT-based radiomics model for predicting renal capsule invasion in renal cell carcinoma

基于CT的放射组学模型预测肾细胞癌肾包膜侵犯

Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes

基于放射影像表型预测乳腺肿瘤微环境中的细胞侵袭

Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics

利用多参数肝脏MRI放射组学进行术前微血管侵犯预测

MS-2 Minimally invasive glioma surgery with navigation system and tubular retractor

MS-2 微创胶质瘤手术，配备导航系统和管状牵开器

The Role of Single Voxel MR Spectroscopy, T2 Relaxation Time and Apparent Diffusion Coefficient in Determining the Cellularity of Brain Tumors by MATLAB Software

利用MATLAB软件分析单体素磁共振波谱、T2弛豫时间和表观扩散系数在确定脑肿瘤细胞密度中的作用