Auto-metric distribution propagation graph neural network with a meta-learning strategy for diagnosis of otosclerosis
Author:
Funder
Innovative Research Group Project of the National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05449-3.pdf
Reference34 articles.
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2. Hoste M, Cabri-Wiltzer M, Hassid S, Degols J-C, Vilain J (2022) Hearing loss due to urate deposition in the middle ear: A case report and literature review. J Otol 17(1):50–53
3. Assiri M, Khurayzi T, Alshalan A, Alsanosi A (2022) Cochlear implantation among patients with otosclerosis: a systematic review of clinical characteristics and outcomes. Eur Arch Otorhinolaryngol 279(7):3327–3339
4. Tan W, Guan P, Wu L, Chen H, Li J, Ling Y, Fan T, Wang Y, Li J, Yan B (2021) The use of explainable artificial intelligence to explore types of fenestral otosclerosis misdiagnosed when using temporal bone high-resolution computed tomography. Ann Transl Med 9(12):1–20
5. Fujima N, Andreu-Arasa VC, Onoue K, Weber PC, Hubbell RD, Setty BN, Sakai O (2021) Utility of deep learning for the diagnosis of otosclerosis on temporal bone ct. Eur Radiol 31(7):5206–5211
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