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

Daily Symptom Home Monitoring Decreases Hospital Readmissions in Children and Young Adults With Acute Lymphoblastic Leukemia

每日症状居家监测可降低急性淋巴细胞白血病患儿和青少年患者的再入院率

期刊:Cancer Medicine
影响因子:3.1
doi:10.1002/cam4.71719
Ben-Kenan, Rotem Fishel; Retson, Laura L; Fodor, Briana; Temkit, M'hamed; Walsh, Alexandra
白血病
细胞生物学
发表日期：2026
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Amplifying signal-to-noise: Responsible use of large language models in radiology publishing

提高信噪比：在放射学出版中负责任地使用大型语言模型

期刊:Clinical Imaging
影响因子:1.5
doi:10.1016/j.clinimag.2025.110679
Song, Albert S; Masutani, Evan M; Tejani, Ali S; Retson, Tara A
发表日期：2026
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Detecting Common Sources of AI Bias: Questions to Ask When Procuring an AI Solution

检测人工智能偏见的常见来源：采购人工智能解决方案时需要提出的问题

期刊:Radiology
影响因子:15.2
doi:10.1148/radiol.230580
Tejani, Ali S; Retson, Tara A; Moy, Linda; Cook, Tessa S
发表日期：2023
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Epithelioid neoplasm of the spinal cord in a child with spinal muscular atrophy treated with onasemnogene abeparvovec

一名患有脊髓性肌萎缩症的儿童，接受了onasemnogene abeparvovec治疗，结果发现其脊髓出现上皮样肿瘤。

期刊:Molecular Therapy
影响因子:12
doi:10.1016/j.ymthe.2023.08.013
Retson, Laura; Tiwari, Nishant; Vaughn, Jennifer; Bernes, Saunder; Adelson, P David; Mansfield, Keith; Libertini, Silvana; Kuzmiski, Brent; Alecu, Iulian; Gabriel, Richard; Mangum, Ross
神经科学
肿瘤
肿瘤免疫
肌萎缩症
发表日期：2023
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Expanding Horizons: The Realities of CAD, the Promise of Artificial Intelligence, and Machine Learning's Role in Breast Imaging beyond Screening Mammography

拓展视野：计算机辅助诊断的现实、人工智能的前景以及机器学习在乳腺影像学（筛查性乳腺X线摄影之外）中的作用

期刊:Diagnostics
影响因子:3.3
doi:10.3390/diagnostics13132133
Retson, Tara A; Eghtedari, Mohammad
发表日期：2023
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CNN-based Deformable Registration Facilitates Fast and Accurate Air Trapping Measurements at Inspiratory and Expiratory CT

基于卷积神经网络的可变形配准技术可实现吸气和呼气CT扫描中气道阻塞的快速准确测量。

期刊:Radiology-Artificial Intelligence
影响因子:13.2
doi:10.1148/ryai.2021210211
Hasenstab, Kyle A; Tabalon, Joseph; Yuan, Nancy; Retson, Tara; Hsiao, Albert
发表日期：2022
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Erratum: CNN-based Deformable Registration Facilitates Fast and Accurate Air Trapping Measurements at Inspiratory and Expiratory CT

更正：基于 CNN 的可变形配准技术可实现吸气和呼气 CT 扫描中快速、准确地测量气体潴留

期刊:Radiology-Artificial Intelligence
影响因子:13.2
doi:10.1148/ryai.219003
Hasenstab, Kyle A; Tabalon, Joseph; Yuan, Nancy; Retson, Tara; Hsiao, Albert
发表日期：2022
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Reader Perceptions and Impact of AI on CT Assessment of Air Trapping

读者感知及人工智能对CT评估气胸的影响

期刊:Radiology-Artificial Intelligence
影响因子:13.2
doi:10.1148/ryai.2021210160
Retson, Tara A; Hasenstab, Kyle A; Kligerman, Seth J; Jacobs, Kathleen E; Yen, Andrew C; Brouha, Sharon S; Hahn, Lewis D; Hsiao, Albert
发表日期：2022
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Erratum: Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network

勘误：利用深度学习卷积神经网络自动进行慢性阻塞性肺疾病严重程度的CT分期，以预测疾病进展和死亡率

期刊:Radiology-Cardiothoracic Imaging
影响因子:4.2
doi:10.1148/ryct.219002
Hasenstab, Kyle A; Yuan, Nancy; Retson, Tara; Conrad, Douglas J; Kligerman, Seth; Lynch, David A; Hsiao, Albert
慢性阻塞性肺疾病
发表日期：2022
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Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network

利用深度学习卷积神经网络对慢性阻塞性肺疾病严重程度进行自动CT分期，以预测疾病进展和死亡率

期刊:Radiology-Cardiothoracic Imaging
影响因子:4.2
doi:10.1148/ryct.2021200477
Hasenstab, Kyle A; Yuan, Nancy; Retson, Tara; Conrad, Douglas J; Kligerman, Seth; Lynch, David A; Hsiao, Albert
慢性阻塞性肺疾病
发表日期：2021
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