Interdisciplinary data bank in oncoendocrinology. Medullary thyroid cancer and type 2 multiple endocrine neoplasia syndromes
| Autor: | Andrei G. Goncharov, Olga S. Chukhacheva, Konstantin Y. Slashchuk, Sergey V. Korenev, D. G. Beltsevich, Pavel O. Rumiantsev |
|---|---|
| Jazyk: | ruština |
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
endocrine system diseases data bank RD1-811 business.industry Medullary thyroid cancer data mining medicine.disease medullary thyroid cancer Automated control Multiple Endocrine Neoplasia Syndromes Pheochromocytoma Thyroid carcinoma endocrinology oncology medicine multidisciplinary approach Data bank In patient Surgery multiple endocrine neoplasia syndrome business Intensive care medicine Multiple endocrine neoplasia |
| Zdroj: | Эндокринная хирургия, Vol 13, Iss 3, Pp 105-117 (2020) |
| ISSN: | 2310-3965 2306-3513 |
| Popis: | Medullary thyroid cancer (MTC) is about 5% of all thyroid carcinomas and is hereditary in 2030% of cases. Multiple endocrine neoplasia syndrome type 2 (MEN2), in addition to medullary thyroid cancer, may include pheochromocytoma, hyperparathyroidism, and some other manifestations. The multidisciplinary data bank (MDB) developed by us is a specialized resource for storing, accumulating and subsequent analysis of data on patients with MTC and MEN2 syndromes. The MDB allows you to collect data from any sources (primary care, medical institutions at various levels, federal centers) and provides internal automated control of the quality and quantity of input data. It is necessary to keep a record of such data to improve the efficiency of diagnostics, treatment and rehabilitation of patients. MDB is an integrated digital platform containing reference materials for doctors, which allows combining evidence-based clinical experience in patients, and provides the opportunity for expert support of medical decisions. In the long run, it will help us organize digitally stored data for machine learning and lays the groundwork for the development of artificial neural networks. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|