Computed tomography radiomics identification of T1–2 and T3–4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?

Y Li, L Yang, X Gu, Q Wang, G Shi, A Zhang, M Yue… - Abdominal …, 2024 - Springer
Background To evaluate two-dimensional (2D) and three-dimensional (3D) computed
tomography (CT) radiomics analysis for the T stage of esophageal squamous cell carcinoma …

[HTML][HTML] Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed …

C Zhang, H Zhong, F Zhao, ZY Ma, ZJ Dai… - World Journal of …, 2024 - ncbi.nlm.nih.gov
BACKGROUND Recently, vessels encapsulating tumor clusters (VETC) was considered as
a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole …

Extended application of a CT-based artificial intelligence prognostication model in patients with primary lung cancer undergoing stereotactic ablative radiotherapy

H Kim, JH Lee, HJ Kim, CM Park, HG Wu… - Radiotherapy and …, 2021 - Elsevier
Background and purpose To validate a computed tomography (CT)-based deep learning
prognostication model, originally developed for a surgical cohort, in patients with primary …

Preoperatively predicting survival outcome for clinical stage IA pure-solid non–small cell lung cancer by radiomics-based machine learning

H Yan, T Niimi, T Matsunaga, M Fukui, A Hattori… - The Journal of Thoracic …, 2024 - Elsevier
Objective Clinical stage IA non–small cell lung cancer (NSCLC) showing a pure-solid
appearance on computed tomography is associated with a worse prognosis. This study …

Lung Cancer Survival Time Prediction Using Machine Learning and Deep Learning Techniques

QB Baker, E Khwaileh, M Alharbi… - … on Intelligent Data …, 2023 - ieeexplore.ieee.org
Accurate prediction of patient survival is pivotal for discerning prognostic indicators from
radiological imagery. This study addresses the critical task of estimating the survival time of …

The more diagnostic accuracy, the better therapeutic chance: novel insight into lung cancer screening proposal

BT Marinucci, M Ibrahim - European Journal of Cardio-Thoracic …, 2023 - academic.oup.com
Improved radiological techniques over the years have led to increasing levels of accuracy in
diagnostic models. The more and more precise imaging modalities have allowed to detect …

Simple delineations cannot substitute full 3d tumor delineations for MR-based radiomics prediction of locoregional control in oropharyngeal cancer

P Bos, MWM van den Brekel, M Taghavi… - European journal of …, 2022 - Elsevier
Background and purpose Manual delineation of head and neck tumor contours for radiomics
analyses is tedious and time consuming. This study investigates if fast or readily available …

Establishment of a non-squamous cell carcinoma of the larynx nomogram prognostic model and prognosis analysis

L Fan, R Zhao, X Chen, Y Liu, L Tian, M Liu - Auris Nasus Larynx, 2022 - Elsevier
Objective We aimed to compare the prognosis of laryngeal squamous cell carcinoma
(LSCC) and nSCCs of the larynx. Then we established a nomogram for nSCCs of the larynx …

[引用][C] 横纹肌肉瘤患者列线图预后模型的构建

左昊, 陈罗军, 刘华丽, 李娜, 宋启斌 - 中国肿瘤临床, 2019

[HTML][HTML] Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women

Q Li, J Dormer, P Daryani, D Chen… - Proceedings of SPIE …, 2019 - ncbi.nlm.nih.gov
Breast cancer in young women is commonly aggressive, in part because the proportion of
high-grade, triple-negative (TN) tumor is too high. There are certain limitations in the …