Dooman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

文献求助收藏

Human Not in the Loop: Objective Sample Difficulty Measures for Curriculum Learning

人为因素不在决策过程中：课程学习的客观难度衡量指标

期刊:

影响因子:

doi:10.1109/isbi53787.2023.10230597

Zhou, Zhengbo; Luo, Jun; Arefan, Dooman; Kitamura, Gene; Wu, Shandong

Human

发表日期：2023

文献求助收藏

Deep learning of longitudinal mammogram examinations for breast cancer risk prediction

利用深度学习技术预测乳腺癌风险：纵向乳腺X线检查的纵向应用

期刊:Pattern Recognition

影响因子:7.6

doi:10.1016/j.patcog.2022.108919

Dadsetan, Saba; Arefan, Dooman; Berg, Wendie A; Zuley, Margarita L; Sumkin, Jules H; Wu, Shandong

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

Multicenter and prospective trial of anti-epileptics for early seizure prevention in mild traumatic brain injury with a positive computed tomography scan

一项多中心前瞻性试验，研究抗癫痫药物对轻度创伤性脑损伤（CT扫描阳性）患者早期预防癫痫发作的疗效。

期刊:

影响因子:

doi:10.25259/SNI_38_2022

Pease, Matthew; Zaher, Mazen; Lopez, Alejandro J; Yu, Siyuan; Egodage, Tanya; Semroc, Suzan; Arefan, Dooman; Jankowitz, Brian

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study

利用机器学习识别肥胖代谢亚型：一项多中心研究

期刊:Frontiers in Endocrinology

影响因子:4.6

doi:10.3389/fendo.2021.713592

Lin, Ziwei; Feng, Wenhuan; Liu, Yanjun; Ma, Chiye; Arefan, Dooman; Zhou, Donglei; Cheng, Xiaoyun; Yu, Jiahui; Gao, Long; Du, Lei; You, Hui; Zhu, Jiangfan; Zhu, Dalong; Wu, Shandong; Qu, Shen

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

Human Not in the Loop: Objective Sample Difficulty Measures for Curriculum Learning

人为因素不在决策过程中：课程学习的客观难度衡量指标

Deep learning of longitudinal mammogram examinations for breast cancer risk prediction

利用深度学习技术预测乳腺癌风险：纵向乳腺X线检查的纵向应用

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

Multicenter and prospective trial of anti-epileptics for early seizure prevention in mild traumatic brain injury with a positive computed tomography scan

一项多中心前瞻性试验，研究抗癫痫药物对轻度创伤性脑损伤（CT扫描阳性）患者早期预防癫痫发作的疗效。

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study

利用机器学习识别肥胖代谢亚型：一项多中心研究