Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives

NN Zhong, HQ Wang, XY Huang, ZZ Li, LM Cao… - Seminars in Cancer …, 2023 - Elsevier
Head and neck tumors (HNTs) constitute a multifaceted ensemble of pathologies that
primarily involve regions such as the oral cavity, pharynx, and nasal cavity. The intricate …

Artificial intelligence for thyroid nodule characterization: where are we standing?

S Sorrenti, V Dolcetti, M Radzina, MI Bellini, F Frezza… - Cancers, 2022 - mdpi.com
Simple Summary In the present review, an up-to-date summary of the state of the art of
artificial intelligence (AI) implementation for thyroid nodule characterization and cancer is …

Updates on the management of thyroid cancer

KA Araque, S Gubbi… - Hormone and …, 2020 - thieme-connect.com
The diagnostic modalities, stratification tools, and treatment options for patients with thyroid
cancer have rapidly evolved since the development of the American Thyroid Association …

[HTML][HTML] Ai in thyroid cancer diagnosis: Techniques, trends, and future directions

Y Habchi, Y Himeur, H Kheddar, A Boukabou, S Atalla… - Systems, 2023 - mdpi.com
Artificial intelligence (AI) has significantly impacted thyroid cancer diagnosis in recent years,
offering advanced tools and methodologies that promise to revolutionize patient outcomes …

Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records

M Wang, Z Wei, M Jia, L Chen, H Ji - BMC medical informatics and …, 2022 - Springer
Purpose Predictively diagnosing infectious diseases helps in providing better treatment and
enhances the prevention and control of such diseases. This study uses actual data from a …

A comparative analysis of two machine learning-based diagnostic patterns with thyroid imaging reporting and data system for thyroid nodules: diagnostic performance …

CK Zhao, TT Ren, YF Yin, H Shi, HX Wang, BY Zhou… - Thyroid, 2021 - liebertpub.com
Background: The risk stratification system of the American College of Radiology Thyroid
Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is affected by low …

Artificial intelligence for evaluation of thyroid nodules: a primer

FN Tessler, J Thomas - Thyroid, 2023 - liebertpub.com
Background: Artificial intelligence (AI) is broadly defined as the ability of machines to apply
human-like reasoning to problem solving. Recent years have seen a rapid growth of AI in …

Update on ACR TI-RADS: Successes, Challenges, and Future Directions, From the AJR Special Series on Radiology Reporting and Data Systems

JK Hoang, WD Middleton… - American Journal of …, 2021 - Am Roentgen Ray Soc
The American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-
RADS) is an ultrasound-based risk stratification system (RSS) for thyroid nodules that was …

Classification for thyroid nodule using ViT with contrastive learning in ultrasound images

J Sun, B Wu, T Zhao, L Gao, K Xie, T Lin, J Sui… - Computers in biology …, 2023 - Elsevier
The lack of representative features between benign nodules, especially level 3 of Thyroid
Imaging Reporting and Data System (TI-RADS), and malignant nodules limits diagnostic …

The ultrasound risk stratification systems for thyroid nodule have been evaluated against papillary carcinoma. A meta-analysis

P Trimboli, M Castellana, A Piccardo… - Reviews in Endocrine …, 2021 - Springer
Thyroid imaging reporting and data systems (TIRADS) are used to stratify the malignancy
risk of thyroid nodule by ultrasound (US) examination. We conducted a meta-analysis to …