Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study
BACKGROUND: Strategies for integrating artificial intelligence (AI) into thyroid nodule management require additional development and testing. We developed a deep-learning AI model (ThyNet) to differentiate between malignant tumours and benign thyroid nodules and aimed to investigate how ThyNet could help radiologists improve diagnostic performance and avoid unnecessary fine needle aspiration. METHODS: ThyNet was developed and trained on 18 049 images of 8339 patients (training set) from two hos
Record details
Published: 23 March 2021
Source: OpenAlex
Category: Research
Topics: Healthcare · Finance, VC & PE
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
The role of artificial intelligence in healthcare: a structured literature review
OpenAlex · 10 April 2021
Challenges and advances in clinical applications of mesenchymal stromal cells
OpenAlex · 12 February 2021
Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol
OpenAlex · 1 June 2021
Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives
OpenAlex · 22 July 2020
A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss
OpenAlex · 11 December 2021
Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients
OpenAlex · 1 January 2022
How to cite this record
ethics.ai (23 March 2021), “Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study,” evidence record 8953, https://ethics.ai/record/8953 (originally published by OpenAlex).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.