ArticleInternational journal of endocrinology2020
Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder.
Article in International journal of endocrinology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Anxiety, depression and acromegaly: a systematic review.Journal of endocrinological investigation · 2025Pooled it
- Thyroid disease detection using enhanced extreme learning machine based on drop-connect method.Scientific reports · 2026Article
- Multi-omics clustering analysis carries out the molecular-specific subtypes of thyroid carcinoma: implicating for the precise treatment strategies.Genes and immunity · 2025Article
- Semantic consistency generative adversarial network for cross-modality domain adaptation in ultrasound thyroid nodule classification.Applied intelligence (Dordrecht, Netherlands) · 2022Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSeveral commercial tests have been used for the classification of indeterminate thyroid nodules in cytology. However, the geographic inconvenience and high cost confine their widespread use. This study aims to develop a classifier for conveniently clinical utility.
methodsGene expression data of thyroid nodule tissues were collected from three public databases. Immune-related genes were used to construct the classifier with stacked denoising sparse autoencoder.
resultsThe classifier performed well in discriminating malignant and benign thyroid nodules, with an area under the curve of 0.785 [0.638-0.931], accuracy of 92.9% [92.7-93.0%], sensitivity of 98.6% [95.9-101.3%], specificity of 58.3% [30.4-86.2%], positive likelihood ratio of 2.367 [1.211-4.625], and negative likelihood ratio of 0.024 [0.003-0.177]. In the cancer prevalence range of 20-40% for indeterminate thyroid nodules in cytology, the range of negative predictive value of this classifier was 37-61%, and the range of positive predictive value was 98-99%.
conclusionThe classifier developed in this study has the superb discriminative ability for thyroid nodules. However, it needs validation in cytologically indeterminate thyroid nodules before clinical use.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.