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

Machine learning-based treatment outcome prediction in head and neck cancer using integrated noninvasive diagnostics

基于机器学习的头颈癌治疗结果预测:整合无创诊断技术

Yeghaian, Melda; Trebeschi, Stefano; Herrero-Huertas, Marina; Ferradás, Francisco Javier Mendoza; Bos, Paula; van Alphen, Maarten J A; van Gerven, Marcel A J; Beets-Tan, Regina G H; Bodalal, Zuhir; van der Velden, Lilly-Ann

The legend of the response evaluation criteria in solid tumors: A historical overview

实体瘤疗效评价标准的传奇:历史概述

Smesseim, Illaa; Groot Lipman, Kevin B W; Lalezari, Ferry; Burgers, Jacobus A; Trebeschi, Stefano

ESR Essentials: a step-by-step guide of segmentation for radiologists-practice recommendations by the European Society of Medical Imaging Informatics

ESR Essentials:放射科医生分割分步指南——欧洲医学影像信息学会的实践建议

Chupetlovska, Kalina; Akinci D'Antonoli, Tugba; Bodalal, Zuhir; Abdelatty, Mohamed A; Erenstein, Hendrik; Santinha, João; Huisman, Merel; Visser, Jacob J; Trebeschi, Stefano; Groot Lipman, Kevin B W

Multimodal integration of longitudinal noninvasive diagnostics for survival prediction in immunotherapy using deep learning

利用深度学习将纵向无创诊断的多模态整合应用于免疫疗法生存预测

Yeghaian, Melda; Bodalal, Zuhir; van den Broek, Daan; Haanen, John B A G; Beets-Tan, Regina G H; Trebeschi, Stefano; van Gerven, Marcel A J

Prospective validation of an artificial intelligence assessment in a cohort of applicants seeking financial compensation for asbestosis (PROSBEST)

对一组寻求石棉肺经济赔偿的申请人进行人工智能评估的前瞻性验证(PROSBEST)

Smesseim, Illaa; Lipman, Kevin B W Groot; Trebeschi, Stefano; Stuiver, Martijn M; Tissier, Renaud; Burgers, Jacobus A; de Gooijer, Cornedine J

Multi-omics staging of locally advanced rectal cancer predicts treatment response: a pilot study

局部晚期直肠癌的多组学分期预测治疗反应:一项初步研究

Ilaria Cicalini, Antonio Maria Chiarelli, Piero Chiacchiaretta, David Perpetuini, Consuelo Rosa, Domenico Mastrodicasa, Martina d'Annibale, Stefano Trebeschi, Francesco Lorenzo Serafini, Giulio Cocco, Marco Narciso, Antonio Corvino, Sebastiano Cinalli, Domenico Genovesi, Paola Lanuti, Silvia Valenti

A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still lacking?

癌症免疫疗法中基于放射组学的生物标志物层出不穷,为什么仍然缺乏大规模验证?

Ligero, Marta; Gielen, Bente; Navarro, Victor; Cresta Morgado, Pablo; Prior, Olivia; Dienstmann, Rodrigo; Nuciforo, Paolo; Trebeschi, Stefano; Beets-Tan, Regina; Sala, Evis; Garralda, Elena; Perez-Lopez, Raquel

Non-invasive CT radiomic biomarkers predict microsatellite stability status in colorectal cancer: a multicenter validation study

非侵入性CT放射组学生物标志物预测结直肠癌微卫星稳定性状态:一项多中心验证研究

Bodalal, Zuhir; Hong, Eun Kyoung; Trebeschi, Stefano; Kurilova, Ieva; Landolfi, Federica; Bogveradze, Nino; Castagnoli, Francesca; Randon, Giovanni; Snaebjornsson, Petur; Pietrantonio, Filippo; Lee, Jeong Min; Beets, Geerard; Beets-Tan, Regina

Reproducing RECIST lesion selection via machine learning: Insights into intra and inter-radiologist variation

利用机器学习重现RECIST病灶选择:深入了解放射科医生内部和之间的差异

Tareco Bucho, Teresa M; Petrychenko, Liliana; Abdelatty, Mohamed A; Bogveradze, Nino; Bodalal, Zuhir; Beets-Tan, Regina G H; Trebeschi, Stefano

Can blood-based markers predict RECIST progression in non-small cell lung cancer treated with immunotherapy?

血液标志物能否预测接受免疫疗法治疗的非小细胞肺癌的RECIST疾病进展?

Yeghaian, Melda; Tareco Bucho, Teresa M; de Bruin, Melissa; Schmitz, Alexander; Bodalal, Zuhir; Smit, Egbert F; Beets-Tan, Regina G H; van den Broek, Daan; Trebeschi, Stefano