Cargando…

Artificial-intelligence-based computed tomography histogram analysis predicting tumor invasiveness of lung adenocarcinomas manifesting as radiological part-solid nodules

BACKGROUND: Tumor invasiveness plays a key role in determining surgical strategy and patient prognosis in clinical practice. The study aimed to explore artificial-intelligence-based computed tomography (CT) histogram indicators significantly related to the invasion status of lung adenocarcinoma appe...

Descripción completa

Detalles Bibliográficos
Autores principales:	Gao, Jian, Qi, Qingyi, Li, Hao, Wang, Zhenfan, Sun, Zewen, Cheng, Sida, Yu, Jie, Zeng, Yaqi, Hong, Nan, Wang, Dawei, Wang, Huiyang, Yang, Feng, Li, Xiao, Li, Yun
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2023
Materias:	Oncology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996279/ https://www.ncbi.nlm.nih.gov/pubmed/36910632 http://dx.doi.org/10.3389/fonc.2023.1096453

Ejemplares similares

Artificial intelligence system-based histogram analysis of computed tomography features to predict tumor invasiveness of ground-glass nodules
por: Zhang, Huairong, et al.
Publicado: (2023)

A delta-radiomics model for preoperative prediction of invasive lung adenocarcinomas manifesting as radiological part-solid nodules
por: Chen, Wufei, et al.
Publicado: (2022)

Radiological evidence of rapid growth acceleration of a small part solid nodule found to be large-cell carcinoma of the lung
por: Lu, Yunwei, et al.
Publicado: (2023)

Potential of artificial intelligence based on chest computed tomography to predict the nature of part‐solid nodules
por: Ke, Xiaoting, et al.
Publicado: (2023)

Solid Indeterminate Nodules with a Radiological Stability Suggesting Benignity: A Texture Analysis of Computed Tomography Images Based on the Kurtosis and Skewness of the Nodule Volume Density Histogram
por: Borguezan, Bruno Max, et al.
Publicado: (2019)

Artificial intelligence in radiology
por: Jin, Dakai, et al.
Publicado: (2021)

Single‐cell RNA sequencing reveals the multi‐cellular ecosystem in different radiological components of pulmonary part‐solid nodules
por: Li, Yanmeng, et al.
Publicado: (2022)

A radiomics nomogram for invasiveness prediction in lung adenocarcinoma manifesting as part-solid nodules with solid components smaller than 6 mm
por: Zhang, Teng, et al.
Publicado: (2022)

Long‐term follow‐up of persistent pulmonary subsolid nodules: Natural course of pure, heterogeneous, and real part‐solid ground‐glass nodules
por: Zhang, Zhedong, et al.
Publicado: (2023)

The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus
por: Giansanti, Daniele, et al.
Publicado: (2022)

Microscopic Invasions, Prognoses, and Recurrence Patterns of Stage I Adenocarcinomas Manifesting as Part-Solid Ground-Glass Nodules: Comparison With Adenocarcinomas Appearing as Solid Nodules After Matching Their Solid Parts’ Size
por: Hwang, Eui Jin, et al.
Publicado: (2016)

Artificial intelligence in dentomaxillofacial radiology
por: Gokdeniz, Seyide Tugce, et al.
Publicado: (2022)

Implementation of artificial intelligence in the histological assessment of pulmonary subsolid nodules
por: Deng, Jiajun, et al.
Publicado: (2021)

The Artificial Intelligence in Digital Radiology: Part 2: Towards an Investigation of acceptance and consensus on the Insiders
por: Di Basilio, Francesco, et al.
Publicado: (2022)

Distinct tumor bacterial microbiome in lung adenocarcinomas manifested as radiological subsolid nodules
por: Ma, Yi, et al.
Publicado: (2021)

Artificial Intelligence for the Future Radiology Diagnostic Service
por: Mun, Seong K., et al.
Publicado: (2021)

Radiological education in the era of artificial intelligence: A review
por: Wang, Chao, et al.
Publicado: (2023)

Artificial intelligence defines protein-based classification of thyroid nodules
por: Sun, Yaoting, et al.
Publicado: (2022)

The potential impact of artificial intelligence in radiology
por: Paiva, Omir Antunes, et al.
Publicado: (2017)

The ethical adoption of artificial intelligence in radiology
por: Mudgal, Keshav Shree, et al.
Publicado: (2019)

Artificial Intelligence in Radiology—Ethical Considerations
por: Brady, Adrian P., et al.
Publicado: (2020)

Artificial Intelligence in Musculoskeletal Oncological Radiology
por: Vogrin, Matjaz, et al.
Publicado: (2020)

Clinical applications of artificial intelligence in radiology
por: Mello-Thoms, Claudia, et al.
Publicado: (2023)

Object Relocation Visual Tracking Based on Histogram Filter and Siamese Network in Intelligent Transportation
por: Zhang, Jianlong, et al.
Publicado: (2022)

Intraoperative imaging and localization techniques for part-solid nodules
por: Su, Katherine W., et al.
Publicado: (2021)

Apparent diffusion coefficient histogram analysis for differentiating solid ovarian tumors
por: Liu, Renwei, et al.
Publicado: (2022)

Clinical utility of histogram analysis of grayscale sonograms in assessing sonographic suspicious malignant thyroid nodules
por: Zhang, Rui, et al.
Publicado: (2022)

A preliminary glossary of artificial intelligence in radiology
por: Pakdemirli, Emre
Publicado: (2019)

The Potential Dangers of Artificial Intelligence for Radiology and Radiologists
por: Chu, Linda C., et al.
Publicado: (2020)

Prime Time for Artificial Intelligence in Interventional Radiology
por: Seah, Jarrel, et al.
Publicado: (2022)

The augmented radiologist: artificial intelligence in the practice of radiology
por: Sorantin, Erich, et al.
Publicado: (2021)

To pay or not to pay for artificial intelligence applications in radiology
por: Lobig, Franziska, et al.
Publicado: (2023)

Interpretable artificial intelligence in radiology and radiation oncology
por: Cui, Sunan, et al.
Publicado: (2023)

The Teaching Design Methods Under Educational Psychology Based on Deep Learning and Artificial Intelligence
por: Wang, Zewen, et al.
Publicado: (2021)

Total nodule number as an independent prognostic factor in resected stage III non-small cell lung cancer: a deep learning-powered study
por: Chen, Xiuyuan, et al.
Publicado: (2022)

Invasive adenocarcinoma manifesting as pure ground glass nodule with different size: radiological characteristics differ while prognosis remains the same
por: Wang, Zijian, et al.
Publicado: (2021)

The Diagnostic Value of Artificial Intelligence Ultrasound S-Detect Technology for Thyroid Nodules
por: Huang, Peizhen, et al.
Publicado: (2022)

Author Correction: Artificial intelligence defines protein-based classification of thyroid nodules
por: Sun, Yaoting, et al.
Publicado: (2022)

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network
por: Tu, Xiaoguang, et al.
Publicado: (2017)

Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology
por: Alelyani, Magbool, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_075mjng9lv3520ga9ia8mh5ee5