28 research outputs found
Towards Multilingual Coreference Resolution
The current work investigates the problems that occur when coreference resolution is considered as a multilingual task. We assess the issues that arise when a framework using the mention-pair coreference resolution model and memory-based learning for the resolution process are used. Along the way, we revise three essential subtasks of coreference resolution: mention detection, mention head detection and feature selection. For each of these aspects we propose various multilingual solutions including both heuristic, rule-based and machine learning methods. We carry out a detailed analysis that includes eight different languages (Arabic, Catalan, Chinese, Dutch, English, German, Italian and Spanish) for which datasets were provided by the only two multilingual shared tasks on coreference resolution held so far: SemEval-2 and CoNLL-2012. Our investigation shows that, although complex, the coreference resolution task can be targeted in a multilingual and even language independent way. We proposed machine learning methods for each of the subtasks that are affected by the transition, evaluated and compared them to the performance of rule-based and heuristic approaches. Our results confirmed that machine learning provides the needed flexibility for the multilingual task and that the minimal requirement for a language independent system is a part-of-speech annotation layer provided for each of the approached languages. We also showed that the performance of the system can be improved by introducing other layers of linguistic annotations, such as syntactic parses (in the form of either constituency or dependency parses), named entity information, predicate argument structure, etc. Additionally, we discuss the problems occurring in the proposed approaches and suggest possibilities for their improvement
ΠΠ¦ΠΠΠΠ ΠΠ ΠΠΠ£ΠΠΠΠΠ¦ΠΠ―Π’Π Π‘Π ΠΠ©Π£ Π§ΠΠΠΠ¨ΠΠ ΠΠΠΠΠΠΠΠ ΠΠΠ Π£Π‘ ΠΠͺΠ ΠΠΠ ΠΠΠΠ‘ΠΠ Π ΠΠΠΠΠ ΠΠ ΠΠΠ ΠΠΠΠ 2015-2022Π.
Π§ΠΎΠ²Π΅ΡΠΊΠΈΡΡ ΠΏΠ°ΠΏΠΈΠ»ΠΎΠΌΠ΅Π½ Π²ΠΈΡΡΡ (HPV) Π΅ Π½Π°ΠΉ-ΡΠ΅ΡΡΠΎ ΠΏΡΠ΅Π΄Π°Π²Π°Π½Π°ΡΠ° ΠΏΠΎ ΠΏΠΎΠ»ΠΎΠ² ΠΏΡΡ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΡ. ΠΠ΅Π³ΠΎΠ²ΠΈΡΠ΅ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π½ΠΈ ΠΈ ΠΎΠ½ΠΊΠΎΠ³Π΅Π½Π½ΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΡΠ° Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΈΡΠ°Π½ΠΈ ΠΈ Π΅ ΠΈΠ·Π²Π΅ΡΡΠ½ΠΎ, ΡΠ΅ ΠΏΡΠΈΡΠΈΠ½ΠΈΡΠ΅Π»ΡΡ ΡΠ΅ ΡΡΠ΅ΡΠ°, ΠΊΠ°ΠΊΡΠΎ ΠΏΡΠΈ ΠΆΠ΅Π½ΠΈ, ΡΠ°ΠΊΠ° ΠΈ ΠΏΡΠΈ ΠΌΡΠΆΠ΅. ΠΠ°ΡΠ°Π·ΡΠ²Π°Π½Π΅ΡΠΎ ΡΡΠ°Π²Π° ΠΏΡΠ΅Π΄ΠΈΠΌΠ½ΠΎ Π² ΡΠ½ΠΎΡΠ΅ΡΠΊΠ° ΠΈ ΠΌΠ»Π°Π΄Π° Π²ΡΠ·ΡΠ°ΡΡ. ΠΡΠΌ Π΄Π½Π΅ΡΠ½Π° Π΄Π°ΡΠ°,Π² ΡΠ²Π΅ΡΠΎΠ²Π΅Π½ ΠΌΠ°ΡΠ°Π± ΡΠ° Π»ΠΈΡΠ΅Π½Π·ΠΈΡΠ°Π½ΠΈ ΡΠ΅ΡΡ HPV Π²Π°ΠΊΡΠΈΠ½ΠΈ. Π ΠΌΠ½ΠΎΠ³ΠΎ ΡΡΡΠ°Π½ΠΈ Π½ΠΈΠ²ΠΎΡΠΎ Π½Π° Π²Π°ΠΊΡΠΈΠ½Π°ΡΠΈΡ Π΅ Π²ΠΈΡΠΎΠΊΠΎ Π½Π΅ ΡΠ°ΠΌΠΎ ΡΡΠ΅Π΄ ΠΏΠΎΠ΄ΡΠ°ΡΡΠ²Π°ΡΠΈΡΠ΅ ΠΌΠΎΠΌΠΈΡΠ΅ΡΠ°, Π½ΠΎ ΠΈ ΠΌΠΎΠΌΡΠ΅ΡΠ°. ΠΡΠΌ ΠΌΠΎΠΌΠ΅Π½ΡΠ° Π² ΠΡΠ»Π³Π°ΡΠΈΡ ΡΠ΅ ΠΈΠ·ΠΏΡΠ»Π½ΡΠ²Π° ΡΡΠ΅ΡΠ°ΡΠ° ΠΠ°ΡΠΈΠΎΠ½Π°Π»Π½Π° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ° Π·Π° ΠΏΡΡΠ²ΠΈΡΠ½Π° ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠ° Π½Π° ΡΠ°ΠΊΠ° Π½Π° ΠΌΠ°ΡΠΎΡΠ½Π°ΡΠ° ΡΠΈΠΉΠΊΠ°.Π¦Π΅Π»ΡΠ° Π΅ Π΄Π° ΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΠΈ Π΅ΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ½Π° Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° Π½Π° ΠΎΠ±Ρ
Π²Π°Π½Π°ΡΠΈΡΠ΅ Ρ ΠΈΠΌΡΠ½ΠΈΠ·Π°ΡΠΈΡ ΡΡΠ΅ΡΡ HPV ΠΌΠΎΠΌΠΈΡΠ΅ΡΠ° Π²ΡΠ² ΠΠ°ΡΠ½Π΅Π½ΡΠΊΠ° ΠΎΠ±Π»Π°ΡΡ Π·Π° ΠΏΠ΅ΡΠΈΠΎΠ΄Π° 2015-2022 Π³.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»ΠΈ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ. Π Π΅ΡΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π΅Π½ Π°Π½Π°Π»ΠΈΠ· (2015Π³.-2022Π³.) Π½Π° ΠΎΡΠΈΡΠΈΠ°Π»Π½ΠΈ Π΄Π°Π½Π½ΠΈ ΠΎΡ Π³ΠΎΠ΄ΠΈΡΠ½ΠΈΡΠ΅ Π°Π½Π°Π»ΠΈΠ·ΠΈ Π½Π° Π ΠΠ-ΠΠ°ΡΠ½Π°.Π Π΅Π·ΡΠ»ΡΠ°ΡΠΈ ΠΈ Π΄ΠΈΡΠΊΡΡΠΈΡ. ΠΠΎΡΠ°Π΄ΠΈ Π½Π΅Π·Π°Π΄ΡΠ»ΠΆΠΈΡΠ΅Π»Π½ΠΈΡ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ Π½Π° Π²Π°ΠΊΡΠΈΠ½Π°ΡΠ°, ΠΎΡΠΈΡΠΈΠ°Π»Π½ΠΈΡΠ΅ Π΄Π°Π½Π½ΠΈ Π½Π΅ ΡΠ° ΠΏΡΠ»Π½ΠΈ. ΠΡΠ΅Π· 2015Π³. ΡΠ° Π²Π°ΠΊΡΠΈΠ½ΠΈΡΠ°Π½ΠΈ 667 ΠΌΠΎΠΌΠΈΡΠ΅ΡΠ° Π½Π° Π²ΡΠ·ΡΠ°ΡΡ 12-13 Π³ΠΎΠ΄ΠΈΠ½ΠΈ. ΠΠ° ΠΏΠ΅ΡΠΈΠΎΠ΄Π° 2016Π³.- 2019Π³. ΡΡΠ΅Π΄ ΠΎΠ±Ρ
Π²Π°Π½Π°ΡΠΈΡΠ΅ ΠΌΠΎΠΌΠΈΡΠ΅ΡΠ° Ρ Π²Π°ΠΊΡΠΈΠ½Π°ΡΠ° ΡΡΠ΅ΡΡ HPV ΡΠ΅ ΠΎΡΡΠΈΡΠ° ΡΠΏΠ°Π΄ ΠΊΠ°ΡΠΎ Π½Π°ΠΉ-ΠΌΠ°Π»ΠΊΠΎΠ²Π°ΠΊΡΠΈΠ½ΠΈΡΠ°Π½ΠΈ Π΅ ΠΈΠΌΠ°Π»ΠΎ ΠΏΡΠ΅Π· 2018Π³. - 275. ΠΡΠ΅Π· 2020Π³. ΡΠ΅ Π½Π°Π±Π»ΡΠ΄Π°Π²Π° ΠΏΠΎΠΊΠ°ΡΠ²Π°Π½Π΅ Π½Π° Π±ΡΠΎΡ Π½Π° Π²Π°ΠΊΡΠΈΠ½ΠΈΡΠ°ΡΠ΅ ΡΠΏΡΡΠΌΠΎ ΠΏΡΠ΅Π΄Ρ
ΠΎΠ΄Π½ΠΈΡΠ΅ ΡΠ΅ΡΠΈΡΠΈ Π³ΠΎΠ΄ΠΈΠ½ΠΈ - 424, Π½ΠΎ ΠΏΡΠ΅Π· 2022 Π³. Π΅ ΡΠ΅Π³ΠΈΡΡΡΠΈΡΠ°Π½Π° Π½Π°ΠΉ-Π½ΠΈΡΠΊΠ° Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡ Π½Π° ΠΈΠΌΡΠ½ΠΈΠ·Π°ΡΠΈΡΡΠ° ΡΡΠ΅ΡΡ HPV Π·Π° ΡΠ΅Π»ΠΈΡ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΠ°Π½ ΠΏΠ΅ΡΠΈΠΎΠ΄ - 170 ΠΌΠΎΠΌΠΈΡΠ΅ΡΠ°.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΠ°Π±Π΅Π»ΡΠ·Π²Π° ΡΠ΅ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡ ΠΊΡΠΌ ΠΏΠΎΠ½ΠΈΠΆΠ°Π²Π°Π½Π΅ Π½Π° Π±ΡΠΎΡ Π½Π° ΠΎΠ±Ρ
Π²Π°Π½Π°ΡΠΈΡΠ΅ ΠΌΠΎΠΌΠΈΡΠ΅ΡΠ° Ρ Π²Π°ΠΊΡΠΈΠ½Π° ΠΏΡΠΎΡΠΈΠ² ΡΠΎΠ²Π΅ΡΠΊΠΈ ΠΏΠ°ΠΏΠΈΠ»ΠΎΠΌΠ° Π²ΠΈΡΡΡ Π² ΡΠ΅Π³ΠΈΠΎΠ½ ΠΠ°ΡΠ½Π°. Π―Π²Π»Π΅Π½ΠΈΠ΅ΡΠΎ ΡΠ΅ Π΄ΡΠ»ΠΆΠΈ Π½Π°ΠΉ-Π²Π΅ΡΠ΅ Π½Π° ΡΠΈΡΠΎΠΊΠΎ ΡΠ°Π·ΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΡΡΠ΅Π΄ ΠΎΠ±ΡΠ΅ΡΡΠ²ΠΎΡΠΎ Π½Π΅Π³Π°ΡΠΈΠ²ΠΈΠ·ΡΠΌ ΠΊΡΠΌ Π²Π°ΠΊΡΠΈΠ½Π°ΡΠ° ΡΡΠ΅ΡΡ ΡΠ°ΠΊ Π½Π° ΠΌΠ°ΡΠΎΡΠ½Π°ΡΠ° ΡΠΈΠΉΠΊΠ°
Kidney stone disease (Nephrolithiasis) - Pathogenesis, types of imaging diagnostic methods in contemporary medicine
Π ΠΈΡΠΊΡΡ ΠΎΡ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ Π½Π° Π½Π΅ΡΡΠΎΠ»ΠΈΡΠΈΠ°Π·Π° Π² ΡΠ°Π·Π²ΠΈΡΠΈΡΠ΅ ΡΡΡΠ°Π½ΠΈ Π΅ ΠΎΠΊΠΎΠ»ΠΎ 12% ΠΏΡΠΈ ΠΌΡΠΆΠ΅ΡΠ΅ ΠΈ 6% ΠΏΡΠΈ ΠΆΠ΅Π½ΠΈΡΠ΅. ΠΡΠ»Π°ΡΠ° ΡΠ°ΡΠ° Π΅ ΠΏΠΎ-Π·Π°ΡΠ΅Π³Π½Π°ΡΠ° ΠΎΡ ΡΠ΅ΡΠ½Π°ΡΠ°. Π§Π΅ΡΡΠΎΡΠ°ΡΠ° Π½Π° Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½Π΅ΡΠΎ ΡΠ΅ ΡΠ²Π΅Π»ΠΈΡΠ°Π²Π° ΠΏΡΠ°Π²ΠΎΠΏΡΠΎΠΏΠΎΡΡΠΈΠΎΠ½Π°Π»Π½ΠΎ Π½Π° ΡΠ²Π΅Π»ΠΈΡΠ΅Π½Π°ΡΠ° ΡΠ΅ΡΡΠΎΡΠ° Π½Π° Π·Π°Ρ
Π°ΡΠ΅Π½ Π΄ΠΈΠ°Π±Π΅Ρ ΡΠΈΠΏ ΠΠ ΠΈ Π½Π°Π΄Π½ΠΎΡΠΌΠ΅Π½ΠΎΡΠΎ ΡΠ΅Π³Π»ΠΎ. Π‘ΡΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅ΡΠΎ ΠΌΡΠΆΠ΅ / ΠΆΠ΅Π½ΠΈ Π΅ 1,3:1. Π§Π΅ΡΡΠΎΡΠ°ΡΠ° ΡΠ΅ ΡΠ²Π΅Π»ΠΈΡΠ°Π²Π° Π²ΡΠ² Π²ΡΠ·ΡΠ°ΡΡΡΠ° Π½Π°Π΄ 20 Π³ΠΎΠ΄ΠΈΠ½ΠΈ, a ΠΏΠΈΠΊΡΡ Π½Π° ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡΡΠ° Π΅ Π²ΡΠ² Π²ΡΠ·ΡΠ°ΡΡΠΎΠ²Π°ΡΠ° Π³ΡΡΠΏΠ° ΠΌΠ΅ΠΆΠ΄Ρ 40-60 Π³ΠΎΠ΄ΠΈΠ½ΠΈ, ΡΠ»Π΅Π΄ ΠΊΠΎΠ΅ΡΠΎ Π½Π°ΠΌΠ°Π»ΡΠ²Π° ΠΈ ΠΎΡΡΠ°Π²Π° ΠΊΠΎΠ½ΡΡΠ°Π½ΡΠ°. ΠΠ΅ΡΡΠΎΠ»ΠΈΡΠΈΠ°Π·Π°ΡΠ° Π΅ ΠΈΠ·Π²Π΅ΡΡΠ½Π° ΠΎΡΠ΅ ΠΊΠ°ΡΠΎ Π±ΡΠ±ΡΠ΅ΡΠ½ΠΎ-ΠΊΠ°ΠΌΠ΅Π½Π½Π° Π±ΠΎΠ»Π΅ΡΡ ΠΈ ΡΠ΅ ΡΠ°Π·Π²ΠΈΠ²Π° ΠΏΡΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈ Ρ Π³Π΅Π½Π΅ΡΠΈΡΠ½Π° ΠΏΡΠ΅Π΄ΠΈΡΠΏΠΎΠ·ΠΈΡΠΈΡ, ΠΏΡΠΈ ΡΠΈΡΠΎΠΊ ΡΠΏΠ΅ΠΊΡΡΡ ΠΎΡ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠ½ΠΈ Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ, a ΡΡΡΠΎ ΠΈ ΠΏΡΠΈ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²ΠΎ ΠΊΠΎΠΌΠΎΡΠ±ΠΈΠ΄Π½ΠΈ ΡΡΡΡΠΎΡΠ½ΠΈΡ. ΠΠΎΠ²Π΅ΡΠ΅ΡΠΎ ΠΊΠ°ΠΌΡΠ½ΠΈ ΡΠ° ΠΈΠ·Π³ΡΠ°Π΄Π΅Π½ΠΈ ΠΎΡ ΠΊΠ°Π»ΡΠΈΠ΅Π² ΠΎΠΊΡΠ°Π»Π°Ρ ΠΈ ΠΏΠΈΠΊΠΎΡΠ½Π° ΠΊΠΈΡΠ΅Π»ΠΈΠ½Π°, ΡΡΡΡΠ²ΠΈΡ (Π°ΠΌΠΎΠ½ΠΈΠ΅Π²ΠΎ-ΠΌΠ°Π³Π½Π΅Π·ΠΈΠ΅Π² ΡΡΠ»ΡΠ°Ρ), ΡΠΈΡΡΠΈΠ½, Π°ΠΌΠΎΠ½ΠΈΠ΅Π² ΡΡΠ°Ρ. ΠΠ°ΠΏΠΎΡΠ»Π΅Π΄ΡΠΊ ΡΠ΅ ΠΏΠΎΠ²ΠΈΡΠ°Π²Π° ΡΠ΅ΡΡΠΎΡΠ°ΡΠ° Π½Π° Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½ΠΎ ΠΈΠ½Π΄ΡΡΠΈΡΠ°Π½Π°ΡΠ° Π½Π΅ΡΡΠΎΠ»ΠΈΡΠΈΠ°Π·Π°, ΠΊΠΎΡΡΠΎ ΡΠ΅ Π½Π°Π±Π»ΡΠ΄Π°Π²Π° ΠΏΡΠΈ ΠΈΠΌΠΎΠ±ΠΈΠ»ΠΈΠ·ΠΈΡΠ°Π½ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈ.ΠΠ±ΡΠ°Π·Π½ΠΎΠ΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ½ΠΈΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π·Π°ΠΏΠΎΡΠ²Π°Ρ Ρ ΡΠ»ΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΠΎΡΠΎ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½Π΅ Π½Π° ΠΏΠΈΠΊΠΎΡΠΎ-ΠΎΡΠ΄Π΅Π»ΠΈΡΠ΅Π»Π½Π°ΡΠ° ΡΠΈΡΡΠ΅ΠΌΠ°. Π’ΠΎ ΠΎΡΠΊΡΠΈΠ²Π° Π³ΠΎΠ»ΡΠΌ ΠΏΡΠΎΡΠ΅Π½Ρ ΠΎΡ Π²ΡΠΈΡΠΊΠΈ ΠΊΠΎΠ½ΠΊΡΠ΅ΠΌΠ΅Π½ΡΠΈ, ΠΊΠ°ΠΊΡΠΎ ΠΈ ΠΏΠ°ΡΠ΅Π½Ρ
ΠΈΠΌΠ½ΠΈ ΠΏΡΠΎΡΠ΅ΡΠΈ, ΠΊΠΎΠΈΡΠΎ Π±ΠΈΡ
Π° ΠΌΠΎΠ³Π»ΠΈ Π΄Π° ΠΈΠΌΠΈΡΠΈΡΠ°Ρ ΡΠ΅Π½Π°Π»Π½Π° ΠΊΠΎΠ»ΠΈΠΊΠ°. ΠΠ±Π·ΠΎΡΠ½Π°ΡΠ° ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ³ΡΠ°ΡΠΈΡ Π½Π° Π±ΡΠ±ΡΠ΅ΡΠΈ, ΡΡΠ΅ΡΠ΅ΡΠΈ, ΠΏΠΈΠΊΠΎΡΠ΅Π½ ΠΌΠ΅Ρ
ΡΡ (ΠΠ£Π) ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ²Π° ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ²ΠΎ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½Π΅ Π½Π° ΠΎΡΠ΄Π΅Π»ΠΈΡΠ΅Π»Π½Π°ΡΠ° ΡΠΈΡΡΠ΅ΠΌΠ°, ΠΊΠΎΠ΅ΡΠΎ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠ° ΠΊΠΎΠ½ΠΊΡΠ΅ΠΌΠ΅Π½ΡΠΈ Ρ ΠΊΠ°Π»ΡΠΈΠ΅Π²ΠΎ ΡΡΠ΄ΡΡΠΆΠΈΠΌΠΎ; ΠΎΠ±ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΎ ΠΏΡΠ΅Π΄ΡΠ΅ΡΡΠ²Π° Π²Π΅Π½ΠΎΠ·Π½Π°ΡΠ° ΡΡΠΎΠ³ΡΠ°ΡΠΈΡ ΠΈ Π΄ΡΡΠ³ΠΈ ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ²ΠΈ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½ΠΈΡ. ΠΠ΅Π½ΠΎΠ·Π½Π° ΡΡΠΎΠ³ΡΠ°ΡΠΈΡ - ΠΌΠ΅ΡΠΎΠ΄ΡΡ Π΄Π°Π²Π° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΊΠ°ΠΊΡΠΎ Π·Π° ΠΏΠΎΠ·ΠΈΡΠΈΡΡΠ° ΠΈ ΡΠ°Π·ΠΌΠ΅ΡΠ° Π½Π° ΠΊΠΎΠ½ΠΊΡΠ΅ΠΌΠ΅Π½ΡΠ°, ΡΠ°ΠΊΠ° ΠΈ Π·Π° ΡΡΡΡΠΎΡΠ½ΠΈΠ΅ΡΠΎ Π½Π° Π±ΡΠ±ΡΠ΅ΡΠ½Π°ΡΠ° ΡΡΠ½ΠΊΡΠΈΡ. ΠΠ΅ΡΠΎΠ΄ΡΡ ΠΎΠ±Π°ΡΠ΅ ΠΈΠΌΠ° ΡΠΈΡΠΊ ΠΎΡ ΠΈΠ·Π²Π΅ΡΡΠ½Π° Π½Π΅ΡΡΠΎΡΠΎΠΊΡΠΈΡΠ½ΠΎΡΡ. ΠΠΎΠΌΠΏΡΡΡΡΠ½Π° ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡ Π±Π΅Π· ΠΈΠ·ΠΏΠΎΠ»Π·Π²Π°Π½Π΅ Π½Π° ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½Π° ΠΌΠ°ΡΠ΅ΡΠΈΡ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠ° ΠΊΠΎΠ½ΠΊΡΠ΅ΠΌΠ΅Π½ΡΠΈ Π²ΡΠ² Π²ΡΡΠΊΠ° Π΅Π΄Π½Π° ΡΠ°ΡΡ ΠΎΡ ΠΎΡΠ΄Π΅Π»ΠΈΡΠ΅Π»Π½Π°ΡΠ° ΡΠΈΡΡΠ΅ΠΌΠ°.ΠΠΌΠ° ΡΠ΅Π΄ΠΈΡΠ° Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ, ΠΊΠΎΠΈΡΠΎ ΠΌΠΎΠ³Π°Ρ Π΄Π° ΠΈΠΌΠΈΡΠΈΡΠ°Ρ ΡΠΈΠΌΠΏΡΠΎΠΌΠΈΡΠ΅ Π½Π° ΠΠΠ ΠΈ ΠΏΠΎΡΠ°Π΄ΠΈ ΡΠ°Π·ΠΈ ΠΏΡΠΈΡΠΈΠ½Π° Π΅ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΠ΅ Π΄Π° Π±ΡΠ΄Π°Ρ ΠΈΠ·ΠΊΠ»ΡΡΠ΅Π½ΠΈ Π² Ρ
ΠΎΠ΄Π° Π½Π° Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ½ΠΈΡ ΠΏΡΠΎΡΠ΅Ρ. ΠΠ½Π΅Ρ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ΡΠΎ Π½Π° Π½Π°ΡΠΊΠ°ΡΠ° Π΄ΠΎΠΏΡΠΈΠ½Π΅ΡΠ΅ Π·Π° ΠΏΠΎ-Π·Π°Π΄ΡΠ»Π±ΠΎΡΠ΅Π½ΠΎ ΡΠ°Π·Π±ΠΈΡΠ°Π½Π΅ Π½Π° ΠΏΡΠΈΡΠΈΠ½ΠΈΡΠ΅ ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΈΡΠ΅ Π·Π° ΠΎΠ±ΡΠ°Π·ΡΠ²Π°Π½Π΅ Π½Π° ΠΊΠ°ΠΌΡΠ½ΠΈ ΠΈ ΡΡΠΎΡΠ²Π΅ΡΠ½ΠΎ - Π·Π° ΠΌΠ½ΠΎΠ³ΠΎ ΠΏΠΎ-Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ ΠΊΠ»ΠΈΠ½ΠΈΡΠ½ΠΎ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠΈΡΠ°Π½Π΅ ΠΈ Π»Π΅ΡΠ΅Π½ΠΈΠ΅. ΠΠ΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ Π΅ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΈΡΠ½ΠΎ Π΄Π° ΡΠ΅ ΡΠ»Π΅Π΄ΠΈ Π·Π΄ΡΠ°Π²ΠΎΡΠ»ΠΎΠ²Π½ΠΎΡΠΎ ΡΡΡΡΠΎΡΠ½ΠΈΠ΅ ΡΡΠ΅Π· ΡΠ΅Π΄ΠΎΠ²Π½ΠΈ ΠΊΠΎΠ½ΡΡΠ»ΡΠ°ΡΠΈΠΈ Ρ Π½Π΅ΡΡΠΎΠ»ΠΎΠ³ ΠΈΠ»ΠΈ ΡΡΠΎΠ»ΠΎΠ³, ΠΊΠΎΠΉΡΠΎ Π΄Π° ΠΈΠ·Π²ΡΡΡΠ²Π° Π΅Ρ
ΠΎΠ³ΡΠ°ΡΡΠΊΠΎ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½Π΅.The risk of nephrolithiasis in developed countries is roughly 12% in men and 6% in women. Caucasians are more likely to form kidney stones than black people. The frequency of this pathology increases proportionally to the rising frequency of type II diabetes mellitus and obesity. The ratio of male to female sufferers is 1.3:1. The disease is mostly observed in individuals over the age of 20, while the pique is between 40 and 60 years. Nephrolithiasis is more commonly known as kidney stone disease and develops primarily in genetically predisposed patients, patients with metabolic disorders, and multiple comorbidities. Most stones are made up of calcium oxalate and uric acid, struvite (magnesium ammonium phosphate), cystine, ammonium urate. Recently there has been an increase in medicamentation-induced nephrolithiasis, observed in immobilized patients.The imaging diagnostics begins with abdominal ultrasonography - it can find a large percentage of all calculi, as well as parenchymal processes which could simulate a renal colic. Plain abdominal radiographs can demonstrate calcium-containing stones, and usually precedes venous urograms and other exams. Venous urograms provide insight into a calculus position, as well as regarding renal function. It is, however, associated with potential nephrotoxicity. Computed tomography can natively (without contrast material) demonstrate virtually all stones in every part of the excretory system.There are several conditions which mimic the symptoms of kidney stone disease, and must therefore be exlcuded along the diagnostic pathway. Currently, advanced understanding of the reasons and mechanisms of calculus formation have contributed to more effective diagnostic and treatment methods. Periodic consultations and ultrasonographies with a nephrologist or urologist are advisable
Imaging diagnostic methods for colorectal cancer in contemporary medicine. Types and prevention
INTRODUCTION: Colon cancer (colorectal carcinoma) is a malignant tumor, stemming from the wall of the colon. It is the second most common carcinoma in men (after pulmonary and before stomach cancers) and the third most common in women (after breast and uterine carcinomas). Its frequency has been increasing steadily in the last years. It most often affects people past 50 years of age, but about 20% of cases occur before that point. Histologically, 80% of cases are of adenocarcinoma and about 20% - mucinous. Carcinomas generally develop on the basis of adenomas.AIM: To examine the types, the prevention and the imaging diagnostic methods for the cancer of the large intestine and of the colon of modern medicine.MATERIALS AND METHODS: This research applies statistical methods. The data was processed through statistical and graphical analyses.RESULTS: Screening methods applied with success are as follows: rectoromanoscopy, fibrocolonoscopy, irigography, computed tomographic colonography, magnetic resonance tomography. The most frequently used two are irigography with a barium enema and fibrocolonoscopy. The former allows for a thorough radiological topographical analysis of the whole colon, while the latter allows for direct mucosal visualization and biopsy (both cytological and histological) without radiation by means of a flexible metallic tube inserted retrogradely. Fibrocolonoscopy enables minor minimally invasive surgery such as polyp and small tumor removal. Rectoromanoscopy is a dated method, solely with historical significance. The latest imaging diagnostic methods are the tomographic ones - computed tomography, computed tomography virtual colonoscopy, and magnetic resonance tomography. They are highly informative for all diseases of the colon, contributing considerably to tumor staging, and to preoperative assessment.CONCLUSIONS: Screening programs, timely consultations with specialists and the increasing availability of imaging diagnostic equipment lead to a marked tendency of decreasing colorectal carcinoma mortality in Bulgaria
The effect of X-ray radiation on the human body - pros and cons. Radiation protection in medical imaging and radiotherapy
INTRODUCTION: The discovery of X-rays in November 1895 by Roentgen opened a new chapter in the scientifΒic development and pretty soon it became clear that these rays can be useful for diagnostics and treatment. The most frequent use of X-rays is related to their ability to pass through matter. The main fields of application of the rays are medicine, industry, checks of goods and packages and scientific studies. Modern medicine constiΒtutes approximately 80% of the overexposure. The contribution of diagnostic radiology is approximately 22% of the total exposure of Bulgarian population. The quality of the medical services depends to a great extent on the accurate and timely diagnoses set through different methods using also ionizing radiation. The exposure of the patient should be reasonably justified and optimized but cannot be limited. The risk of exposure to high doses of radiation is justified only if this is appropriate for the diagnosis or the treatment. Each overexposure, including medical irradiation, is related to certain radiation risk. Radiation protection is a means to apply the measures intended to protect the health from ionizing radiation-related risks. It is essential to know the beneΒfits and risks of the medical procedures.AIM: To investigate radiation protection means, and the benefits and risks of medical procedures.MATERIALS AND METHODS: An analysis of literature sources was conducted.RESULTS: The medical control of the radiation protection divides exposure into three categories: professional exposure, medical exposure and exposure of the population. Irradiation by any source should be conducted by optimizing the protection and the safety, maintaining the size of the individual dose, the number of exposed persons and the exposure at levels as low as reasonably achievable considering the social and economic factors. This is the so-called optimization of the protection
Gallstone disease (Cholelithiasis) - pathogenesis, prevention and contemporary methods of imaging diagnostics
INTRODUCTION: Cholelithiasis is a metabolic disorder, leading to stone formation in the bile ducts and gallΒbladder. The stones are classified by their composition as cholesterol, pigment, and mixed. The condition is more frequent in overweight individuals, with a stationary way of life, diabetics, and women on oral contracepΒtives. There is a female predilection with a 3.5:1 ratio. The disease has several forms. The latent one is devoid of complaints - stones are an incidental finding. The acute form manifests with right upper quadrant pain. BiliΒary colic is typical - it comes in fits of right subcostal pain, nausea, and frequently - vomiting. Complications are frequent - gallbladder and bile duct inflammation, biliary obstruction, gallbladder perforation, and biliΒary peritonitis.AIM: To analyze the pathogenesis, the prevention and the modern medical imaging methods related to the gallstones disease.MATERIALS AND METHODS: This research applied statistical methods. The data was processed through staΒtistical and graphical analysis.RESULTS: Accurate diagnosis requires a compound approach. Anamnesis of biliary colic initiates it. AbdomiΒnal ultrasonography is the fastest and most accessible imaging method for finding gallstones. It can also presΒent the gallbladder itself - whether it is enlarged, inflamed, or folded. Additional methods include magnetic resonance imaging (MRI), computed tomography (CT), and some hybrid techniques. If the data of cholelithiΒasis is ambiguous, the latter can be confirmed by endoscopic retrograde cholangiopancreatography (ERCP) - an endoscope is introduced to the level of the papilla of Vater, and contrast is injected into it. The biliary pathΒways also used to be imaged by percutaneous transhepatic cholangiography, which now is a dated technique.CONCLUSIONS: Prophylaxis includes avoiding risk factors of alimentary nature and undergoing periodic conΒtrol ultrasonographies, especially in individuals with a family history of gallstones. This is crucial, as chroni
Beauty today β natural or acquired
Since antiquity beauty has been one of the main aims of mankind. We have a great variety of options for reaching it, some of them completely harmless and others a bit more radical. Provoked by the outburst of role models we decided to check whether they actually have any influence. The goal of our research is to determine the public attitudes about aesthetic procedures. The subjects of our online survey are 244 women between 15 and 65 years of age, from all over Bulgaria. According to a significant part (65.16%) a βpretty womanβ is the one who takes care of her natural look and no one appears to include plastic surgery in this definition. More than the half of them (52.87%) would not change anything and more than one quarter (26.64%) consider there is a huge marketing manipulation about the eventual consequences. Mostly young ladies are willing to go for aesthetic manipulations and a small but an important part of them (4.26%) admit they aim to attract the attention of others. Whether this propaganda has any impact on the society, the possible presence of any vulnerable groups and whether we have enough information about all the procedures on the market are among the questions we will try to answer with our research
Multilinguale Koreferenz-Resolution
The current work investigates the problems that occur when coreference resolution is considered as a multilingual task. We assess the issues that arise when a framework using the mention-pair coreference resolution model and memory-based learning for the resolution process are used. Along the way, we revise three essential subtasks of coreference resolution: mention detection, mention head detection and feature selection. For each of these aspects we propose various multilingual solutions including both heuristic, rule-based and machine learning methods. We carry out a detailed analysis that includes eight different languages (Arabic, Catalan, Chinese, Dutch, English, German, Italian and Spanish) for which datasets were provided by the only two multilingual shared tasks on coreference resolution held so far: SemEval-2 and CoNLL-2012. Our investigation shows that, although complex, the coreference resolution task can be targeted in a multilingual and even language independent way. We proposed machine learning methods for each of the subtasks that are affected by the transition, evaluated and compared them to the performance of rule-based and heuristic approaches. Our results confirmed that machine learning provides the needed flexibility for the multilingual task and that the minimal requirement for a language independent system is a part-of-speech annotation layer provided for each of the approached languages. We also showed that the performance of the system can be improved by introducing other layers of linguistic annotations, such as syntactic parses (in the form of either constituency or dependency parses), named entity information, predicate argument structure, etc. Additionally, we discuss the problems occurring in the proposed approaches and suggest possibilities for their improvement