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

AI Do's and Don'ts in Cancer Imaging: Remembering the Patient Behind the Pixel

癌症影像中的人工智能应用指南:像素背后的患者

Zandieh, Ghazal; Singh, Yashbir; DeSilvio, Thomas; Flannery, Brennan

Empirical evaluation of variability and multi-institutional generalizability of deep learning survival models: application to renal cancer CT scans

深度学习生存模型变异性和多机构泛化能力的实证评估:以肾癌CT扫描为例

Flannery, Brennan; DeSilvio, Thomas; Hariri, Mohsen; Sadri, Amir Reza; Heller, Nicholas; Weight, Christopher; Viswanath, Satish E

CMS subtypes correlate with complete response in trial of neoadjuvant Galunisertib plus chemoradiation in rectal cancer

CMS亚型与新辅助Galunisertib联合放化疗治疗直肠癌的试验中完全缓解相关

Rajamanickam, Venkatesh; Simons, Noah D; Rosales, Wesley; Kravchenko, Anton; Yamazaki, Tomoko; Bernard, Brady; Piening, Brian; Domingo, Enric; Maughan, Timothy; Alvarez-Jimenez, Charlems; Desilvio, Thomas; Viswanath, Satish; Whiteford, Mark; Hayman, Amanda; O'Brien, David; Kiely, Maria X; Ahmad, Rehan; Gough, Michael J; Crittenden, Marka R; Young, Kristina H

Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging

用于从医学图像中优化识别稳健且可区分特征的变异性正则化特征选择(VaRFS)

Sadri, Amir Reza; Azarianpour, Sepideh; Chirra, Prathyush; Singh, Sneha; DeSilvio, Thomas; Madabhushi, Anant; Viswanath, Satish E

A novel structural modeling magnitude and orientation radiomic descriptor for evaluating response to neoadjuvant therapy in rectal cancers via MRI

一种用于评估直肠癌新辅助治疗反应的新型结构建模幅度和方向放射组学描述符(基于磁共振成像)

Alvarez-Jimenez, Charlems; Antunes, Jacob T; DeSilvio, Thomas; Wei, Zhouping; Ismail, Marwa; Willis, Joseph E; Steinhagen, Emily; Purysko, Andrei; Liska, David; Krishnamurthi, Smitha; Crittenden, Marka; Gough, Michael; Young, Kristina; Madabhushi, Anant; Romero, Eduardo; Tiwari, Pallavi; Viswanath, Satish E

CohortFinder: an open-source tool for data-driven partitioning of digital pathology and imaging cohorts to yield robust machine-learning models

CohortFinder:一款开源工具,用于对数字病理和影像队列进行数据驱动的划分,以生成稳健的机器学习模型

Fan, Fan; Martinez, Georgia; DeSilvio, Thomas; Shin, John; Chen, Yijiang; Jacobs, Jackson; Wang, Bangchen; Ozeki, Takaya; Lafarge, Maxime W; Koelzer, Viktor H; Barisoni, Laura; Madabhushi, Anant; Viswanath, Satish E; Janowczyk, Andrew

Safety Analyses of the Phase 3 VISION Trial of [(177)Lu]Lu-PSMA-617 in Patients with Metastatic Castration-resistant Prostate Cancer

[(177)Lu]Lu-PSMA-617 治疗转移性去势抵抗性前列腺癌患者的 3 期 VISION 试验安全性分析

Chi, Kim N; Armstrong, Andrew J; Krause, Bernd J; Herrmann, Ken; Rahbar, Kambiz; de Bono, Johann S; Adra, Nabil; Garje, Rohan; Michalski, Jeff M; Kempel, Mette M; Fizazi, Karim; Morris, Michael J; Sartor, Oliver; Brackman, Marcia; DeSilvio, Michelle; Wilke, Celine; Holder, Geoffrey; Tagawa, Scott T

Health-related quality of life and pain outcomes with [(177)Lu]Lu-PSMA-617 plus standard of care versus standard of care in patients with metastatic castration-resistant prostate cancer (VISION): a multicentre, open-label, randomised, phase 3 trial

VISION 研究:一项多中心、开放标签、随机、3 期临床试验,旨在评估 [(177)Lu]Lu-PSMA-617 联合标准治疗与单纯标准治疗在转移性去势抵抗性前列腺癌患者中的健康相关生活质量和疼痛结局。

Fizazi, Karim; Herrmann, Ken; Krause, Bernd J; Rahbar, Kambiz; Chi, Kim N; Morris, Michael J; Sartor, Oliver; Tagawa, Scott T; Kendi, Ayse T; Vogelzang, Nicholas; Calais, Jeremie; Nagarajah, James; Wei, Xiao X; Koshkin, Vadim S; Beauregard, Jean-Mathieu; Chang, Brian; Ghouse, Ray; DeSilvio, Michelle; Messmann, Richard A; de Bono, Johann

Lutetium-177-PSMA-617 for Metastatic Castration-Resistant Prostate Cancer

镥-177-PSMA-617 用于转移性去势抵抗性前列腺癌

Sartor, Oliver; de Bono, Johann; Chi, Kim N; Fizazi, Karim; Herrmann, Ken; Rahbar, Kambiz; Tagawa, Scott T; Nordquist, Luke T; Vaishampayan, Nitin; El-Haddad, Ghassan; Park, Chandler H; Beer, Tomasz M; Armour, Alison; Pérez-Contreras, Wendy J; DeSilvio, Michelle; Kpamegan, Euloge; Gericke, Germo; Messmann, Richard A; Morris, Michael J; Krause, Bernd J

A review of machine learning in obesity

机器学习在肥胖症治疗中的应用综述

DeGregory, K W; Kuiper, P; DeSilvio, T; Pleuss, J D; Miller, R; Roginski, J W; Fisher, C B; Harness, D; Viswanath, S; Heymsfield, S B; Dungan, I; Thomas, D M