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Pigolkin Yu.I.

I.M. Sechenov First Moscow State Medical University (Sechenov University)

Kosukhina O.I.

Russian University of Medicine;
Russian Customs Academy

Fomina E.E.

Tver State Technical University

Leonov S.V.

Russian University of Medicine;
th Main State Centre for Forensic Medical and Criminalistic Expertise

Turbachkin V.Yu.

OOO «BARS-International»

Leonova E.N.

I.M. Sechenov First Moscow State Medical University (Sechenov University)

Innovations in forensic medicine: accuracy, evidence and effectiveness of expertises in emergencies in case of mass fatality

Authors:

Pigolkin Yu.I., Kosukhina O.I., Fomina E.E., Leonov S.V., Turbachkin V.Yu., Leonova E.N.

More about the authors

Journal: Forensic Medical Expertise. 2024;67(4): 22‑26

DOI: 10.17116/sudmed20246704122

Read: 953 times

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Table of contents

INNOVATIONS IN FORENSIC MEDICINE: ACCURACY, EVIDENCE AND EFFECTIVENESS OF EXPERTISES IN EMERGENCIES IN CASE OF MASS FATALITY
INNOVATIONS IN FORENSIC MEDICINE: ACCURACY, EVIDENCE AND EFFECTIVENESS OF EXPERTISES IN EMERGENCIES IN CASE OF MASS FATALITY

To cite this article:

Pigolkin YuI, Kosukhina OI, Fomina EE, Leonov SV, Turbachkin VYu, Leonova EN. Innovations in forensic medicine: accuracy, evidence and effectiveness of expertises in emergencies in case of mass fatality. Forensic Medical Expertise. 2024;67(4):22‑26. (In Russ.)
https://doi.org/10.17116/sudmed20246704122

Подписка 2026 Судебно-медицинская экспертиза (Forensic Medical Expertise)
 
МСФ на ЯМ
Использование инфографики авторами научных работ
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Abstract:

The article presents the main innovative methods used in forensic expert practice at the current stage, reveals the principle and algorithms of the developed software complex for registration and identification of the deceased. The proposed program automatically generates four documents, which reduces the time required for forensic expertise in the conditions of mass admission of deceased. The article’s authors substantiate prospects of further application of computer technologies in forensic practice to improve organizational and methodological activities in emergencies with a large number of deceased.

Keywords:

forensic expertise
identification of personality
IT-technologies
software complex
3D-scanning

Authors:

Pigolkin Yu.I.

I.M. Sechenov First Moscow State Medical University (Sechenov University)

Kosukhina O.I.

Russian University of Medicine;
Russian Customs Academy

Fomina E.E.

Tver State Technical University

Leonov S.V.

Russian University of Medicine;
th Main State Centre for Forensic Medical and Criminalistic Expertise

Turbachkin V.Yu.

OOO «BARS-International»

Leonova E.N.

I.M. Sechenov First Moscow State Medical University (Sechenov University)

Received:

27.02.2024

Accepted:

16.04.2024

Close metadata

References:

  1. Ivanov PL, Shcherbakova EV, Pigolkin YuI. Practical use of the molecular-genetic technologies in solving the tasks of forensic medical identification of remains in emergencies with huge human death toll. Forensic Medical Expertise. 2004;47(5):31-40. (In Russ.).
  2. Pigolkin YuI, Dubrovin IA, Dallakyan VF, Mosoyan AS, Khachaturian BS, Bychkov AA. Features of traumatic fragmentation of the body and identification of personality in mass casualties in cases of man-made emergencies. Vestnik Baltijskogo federal’nogo universitetaim. I. Kanta. Seriya: Estestvennyeimedicinskienauki. 2014;7:134-141. (In Russ.).
  3. Pigolkin UI, Nikolenko VN, Zolotenkova GV, Dallakian VPh. Morphological methods in establishment of common and specific signs in forensic identification of personality (review). Saratovskijnauchno-medicinskij zhurnal. 2012;8(4):900-905. (In Russ.).
  4. «Proizvoditel’nost’ truda.E’ffektivnost’ truda. KPI (Key Performance Indicator) — klyuchevy’epokazatelie’ffektivnosti». Accessed June 10, 2024. (In Russ.). https://fbru.turbopages.org/turbo/fb.ru/s/article/456653/proizvoditelnost-truda-effektivnost-truda-kpi-key-performance-indicator-klyuchevyie-pokazateli-effektivnosti
  5. Leonov SV, Shakiryanova YP, Avdeev AI, Kosukhina OI. Modern aspects of personality identification in forensic medicine and criminalistics. Dalnevostochnyjmedicinskijzhurnal. 2022;3:104-111. (In Russ.). https://doi.org/10.35177/1994-5191-2022-3-17
  6. Fomina EE, Zvyagin VN, Narina NV, Usacheva LL. A software package for marking and unified description of an individual’s face from a photo image. Programmny’eprodukty’ isistemy’. 2021;4:660-666. (In Russ.). https://doi.org/10.15827/0236-235X.136.660-666
  7. Zolotenkova GV, Gridina NV, Solodovnikov VI, Trufanov MI, Pigolkin YuI. Calculation of an individual’s biological age with the use of the latest information technologies and construction of a promising intellectual hardware and software complex. Forensic Medical Expertise. 2019;62(3):42-47. (In Russ.). https://doi.org/10.17116/sudmed20196203142
  8. Guryleva ME, Nezhmetdinova FT. Telemedicine: advantages and risks. Medicinskaya etika. 2022;10(1):4-9. (In Russ.). https://doi.org/10.24075/medet.2022.039
  9. Doumbouya MB, Kamsu-Foguem B, Kenfack H, Foguem C. Telemedicine using mobile telecommunication: Towards syntactic interoperability in teleexpertise. Telematics and informatics. 2014;31(4):648-659.  https://doi.org/10.1016/j.tele.2014.01.003
  10. Erofeev SV, Fedorova AS, Kovalev AV, Shishkin YuYu, Fetisov VA. Three-dimensional scanning of the forensic medical objects: the instrumental support and peculiarities of the technology. Forensic Medical Expertise. 2018;61(6):39-42. (In Russ.).
  11. Ritschl LM, Wolff KD, Erben P, Grill FD. Simultaneous, radiation-free registration of the dentoalveolar position and the face by combining 3D photography with a portable scanner and impression-taking. Head & face medicine. 2019;15(1):1-9.  https://doi.org/10.1186/s13005-019-0212-x
  12. Buck U, Buße K, Campana L, Schyma C. Validation and evaluation of measuring methods for the 3D documentation of external injuries in the field of forensic medicine. International journal of legal medicine. 2018;132:551-561.  https://doi.org/10.1007/s00414-017-1756-6
  13. Duraes M, Akkari M, Jeandel C, Moreno B, Subsol G, Duflos C, Captier G. Dynamic three‐dimensional virtual environment to improve learning of anatomical structures. Anatomical sciences education. 2022;15(4):754-764.  https://doi.org/10.1002/ase.2158
  14. Ebert LC, Ptacek W, Breitbeck R, Fürst M, Kronreif G, Martinez RM, Thali M, Flach PM. Virtobot 2.0: the future of automated surface documentation and CT-guided needle placement in forensic medicine. Forensic science, medicine, and pathology. 2014;10(2):179-186.  https://doi.org/10.1007/s12024-013-9520-9
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