ArticleJournal of pathology informatics2022
Mathematical model for preoperative differential diagnosis for the parathyroid neoplasms.
Article in Journal of pathology informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Comparing deep-learning, radiomics, and fusion models for parathyroid tumor classification using ultrasound: a multicenter retrospective study.Quantitative imaging in medicine and surgery · 2026Article
- Machine learning for modeling and identifying risk factors of pancreatic fistula.World journal of gastrointestinal oncology · 2025Article
- An explainable radiomics-based machine learning model for preoperative differentiation of parathyroid carcinoma and atypical tumors on ultrasound: a retrospective diagnostic study.Frontiers in endocrinology · 2025Article
- Update on the current management of persistent and recurrent primary hyperparathyroidism after parathyroidectomy.World journal of clinical cases · 2023Review
- The Russian registry of primary hyperparathyroidism, latest update.Frontiers in endocrinology · 2023Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objective: Preoperative diagnosis of parathyroid carcinoma (PC) is critical for the determination of the scope of surgical intervention. Nowadays, specific diagnostic markers for differentiation of PC and benign tumors are unknown, and less than half of patients with PC undergo necessary Methods: A multi-center retrospective study included 242 patients with primary hyperparathyroidism: 50 patients with PC, 30 with аtypical adenoma (AA), and 162 with adenoma of the parathyroid glands. Results: Patients with PC and AA had higher levels of PTH, ionized and albumin-corrected calcium, ALP, volume and the largest diameter of neoplasm, and the higher frequency of GFR decrease less than 60 ml/min/1.73 m Conclusions: Model can predict adenoma with PPV 100% and PC with PPV 81-92%. Using model clinicians could plan extended
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