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 …

Artificial intelligence in thyroid field—a comprehensive review

F Bini, A Pica, L Azzimonti, A Giusti, L Ruinelli… - Cancers, 2021 - mdpi.com
Simple Summary The incidence of thyroid pathologies has been increasing worldwide.
Historically, the detection of thyroid neoplasms relies on medical imaging analysis …

Thyroid disease prediction using selective features and machine learning techniques

R Chaganti, F Rustam, I De La Torre Díez, JLV Mazón… - Cancers, 2022 - mdpi.com
Simple Summary The study presents a thyroid disease prediction approach which utilizes
random forest-based features to obtain high accuracy. The approach can obtain a 0.99 …

[HTML][HTML] Machine learning on thyroid disease: a review

KS Lee, H Park - Frontiers in Bioscience-Landmark, 2022 - imrpress.com
This study reviews the recent progress of machine learning for the early diagnosis of thyroid
disease. Based on the results of this review, different machine learning methods would be …

Radiomics in differentiated thyroid cancer and nodules: explorations, application, and limitations

Y Cao, X Zhong, W Diao, J Mu, Y Cheng, Z Jia - Cancers, 2021 - mdpi.com
Simple Summary Differentiated thyroid cancer (DTC) is the most common endocrine
malignancy with a high incidence rate in females. The COVID-19 epidemic posed an …

Application and prospects of AI-based radiomics in ultrasound diagnosis

H Zhang, Z Meng, J Ru, Y Meng, K Wang - Visual Computing for Industry …, 2023 - Springer
Artificial intelligence (AI)-based radiomics has attracted considerable research attention in
the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique …

Detecting thyroid disease using optimized machine learning model based on differential evolution

P Gupta, F Rustam, K Kanwal, W Aljedaani… - International Journal of …, 2024 - Springer
Thyroid disease has been on the rise during the past few years. Owing to its importance in
metabolism, early detection of thyroid disease is a task of critical importance. Despite …

A machine-learning algorithm for distinguishing malignant from benign indeterminate thyroid nodules using ultrasound radiomic features

XM Keutgen, H Li, K Memeh… - Journal of Medical …, 2022 - spiedigitallibrary.org
Background: Ultrasound (US)-guided fine needle aspiration (FNA) cytology is the gold
standard for the evaluation of thyroid nodules. However, up to 30% of FNA results are …

A deep learning approach for rapid mutational screening in melanoma

RH Kim, S Nomikou, N Coudray, G Jour, Z Dawood… - BioRxiv, 2019 - biorxiv.org
Image-based analysis as a rapid method for mutation detection can be advantageous in
research or clinical settings when tumor tissue is limited or unavailable for direct testing …

Ultrasound-based radiomics analysis for preoperative prediction of central and lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multi …

Y Tong, J Zhang, Y Wei, J Yu, W Zhan, H Xia… - BMC medical …, 2022 - Springer
Background An accurate preoperative assessment of cervical lymph node metastasis (LNM)
is important for choosing an optimal therapeutic strategy for papillary thyroid carcinoma …