Neural network assistant for automated diagnostics and first aid support for eye and skin injuries in emergency situations

Authors

  • Gleb Yu. Shamsudinov Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1 https://orcid.org/0009-0005-5736-0327
  • Veniamin V. Morozov Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1 https://orcid.org/0009-0001-5648-3780
  • Georgiy S. Shirokov Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1 https://orcid.org/0009-0002-0231-2748
  • Vyacheslav Yu. Yarovoy Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1 https://orcid.org/0009-0008-9078-107X
  • Anna K. Mikhaylova Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1 https://orcid.org/0000-0003-3332-3087

DOI:

https://doi.org/10.33408/2519-237X.2026.10-1.107

Keywords:

artificial intelligence, computer vision, first aid, life safety, data analysis

Abstract

Purpose. Development and validation of a deep neural network for computer vision tasks, which, under conditions of limited time and resources, allows for the automatic classification of pathological conditions of the eyes and skin resulting from man-made and natural emergencies, as well as animal and insect bites, and the proposal of a first aid algorithm.

Methods. Development of a deep neural network architecture, training the model on an expanded dataset of images of pathological conditions of the eyes and skin, validation of the results using standard computer vision metrics.

Findings. A deep neural network has been developed that demonstrates high accuracy in classifying eye and skin pathologies, including animal and insect bites, on an expanded dataset. A new approach to automating first aid in emergency situations has been presented, which allows for reducing diagnostic time and increasing accuracy in various conditions, including the Ministry of Emergency Situations' activities to eliminate biological and social risks in disaster zones.

Application field of research. The obtained results can be used to implement the model in first aid systems during emergencies, mobile applications and devices for rescuers, as well as to solve other problems in the field of life safety.

Author Biographies

Gleb Yu. Shamsudinov, Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1

Faculty of Fire Safety Engineers, cadet

Veniamin V. Morozov, Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1

Faculty of Fire Safety Engineers, cadet

Georgiy S. Shirokov, Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1

Department of Information Technology and Computer Modeling of the Scientific and Technical Center, Inspector

Vyacheslav Yu. Yarovoy, Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1

Chair of Fire Tactics and Emergency Rescue Operations, Lecturer

Anna K. Mikhaylova, Federal State Budget Educational Establishment of Higher Vocational Training «The Siberian Fire and Rescue Academy of State Firefighting Service of the Ministry of Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters»; 662972, Russia, Krasnoyarsk Krai, Zheleznogorsk, Severnaya str., 1

Chair of Fire Tactics and Emergency Rescue Operations, Associate Professor

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Journal of Civil Protection, Vol. 10 No. 1

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Published

2026-02-25

How to Cite

Shamsudinov Г. Ю., Morozov В. В., Shirokov Г. С., Yarovoy В. Ю. and Mikhaylova А. К. (2026) “Neural network assistant for automated diagnostics and first aid support for eye and skin injuries in emergency situations”, Journal of Civil Protection, 10(1), pp. 107–117. doi: 10.33408/2519-237X.2026.10-1.107.

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Copyright (c) 2026 Shamsudinov G.Yu., Morozov V.V., Shirokov G.S., Yarovoy V.Yu., Mikhaylova A.K.

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Issue

Vol. 10 No. 1 (2026): Journal of Civil Protection

Section

Technologies and software in the sphere of emergency prevention and elimination

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