Artificial intelligence in ultrasound

YT Shen, L Chen, WW Yue, HX Xu - European Journal of Radiology, 2021 - Elsevier
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Contemporary thyroid nodule evaluation and management

G Grani, M Sponziello, V Pecce… - The Journal of …, 2020 - academic.oup.com
Context Approximately 60% of adults harbor 1 or more thyroid nodules. The possibility of
cancer is the overriding concern, but only about 5% prove to be malignant. The widespread …

Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study

S Peng, Y Liu, W Lv, L Liu, Q Zhou, H Yang… - The Lancet Digital …, 2021 - thelancet.com
Background Strategies for integrating artificial intelligence (AI) into thyroid nodule
management require additional development and testing. We developed a deep-learning AI …

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 …

Ultrasonography of superficial soft-tissue masses: society of radiologists in ultrasound consensus conference statement

JA Jacobson, WD Middleton, SJ Allison, N Dahiya… - Radiology, 2022 - pubs.rsna.org
The Society of Radiologists in Ultrasound convened a panel of specialists from radiology,
orthopedic surgery, and pathology to arrive at a consensus regarding the management of …

A generic deep learning framework to classify thyroid and breast lesions in ultrasound images

YC Zhu, A AlZoubi, S Jassim, Q Jiang, Y Zhang… - Ultrasonics, 2021 - Elsevier
Breast and thyroid cancers are the two common cancers to affect women worldwide.
Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast …

Performance of contrast-enhanced ultrasound in thyroid nodules: review of current state and future perspectives

M Radzina, M Ratniece, DS Putrins, L Saule… - Cancers, 2021 - mdpi.com
Simple Summary Ultrasound has been used as baseline imaging for thyroid nodules for
decades; nevertheless, no single feature is sensitive or specific enough to exclude or …

[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 …

Machine intelligence in non-invasive endocrine cancer diagnostics

NM Thomasian, IR Kamel, HX Bai - Nature Reviews Endocrinology, 2022 - nature.com
Artificial intelligence (AI) has illuminated a clear path towards an evolving health-care
system replete with enhanced precision and computing capabilities. Medical imaging …

Preoperative CT-based deep learning model for predicting disease-free survival in patients with lung adenocarcinomas

H Kim, JM Goo, KH Lee, YT Kim, CM Park - Radiology, 2020 - pubs.rsna.org
Background Deep learning models have the potential for lung cancer prognostication, but
model output as an independent prognostic factor must be validated with clinical risk factors …