AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems

Umerenkov, Dmitriy; Nesterov, Alexandr; Shaposhnikov, Vladimir; Abramov, Ruslan; Romanenko, Nikolay; Kokh, Vladimir; Kirina, Marina; Abrosimov, Anton; Dylov, Dmitry V.; Oseledets, Ivan

doi:10.24963/ijcai.2025/1098

AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems

Dmitriy Umerenkov, Alexandr Nesterov, Vladimir Shaposhnikov, Ruslan Abramov, Nikolay Romanenko, Vladimir Kokh, Marina Kirina, Anton Abrosimov, Dmitry V. Dylov, Ivan Oseledets

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. AI and Social Good. Pages 9880-9889.

https://doi.org/10.24963/ijcai.2025/1098

Keywords

Natural Language Processing: General
Machine Learning: General
Humans and AI: General

Abstract

Clinical Decision Support Systems (CDSS) play an increasingly important role in medical diagnostics. We present AI Diagnostic Assistant (AIDA), a real-time predictive model designed to assist doctors in interpreting patient conditions. AIDA analyzes electronic health records (EHR), including medical history, laboratory results, and complaints, to suggest potential diagnoses from 95 common conditions before the doctor makes the final decision. The model acts as a verification and backup tool, ensuring that no critical details are overlooked. Trained on 1.5 million patient records and validated on a dataset curated by a panel of experts, AIDA proves trustworthy as a diagnosis-making assistant (87.7% accuracy compared to 91.7% accuracy among doctors).

Integrated into a megapolis-wide CDSS, AIDA has assisted doctors in over 3 million real-world diagnoses to date.

Dmitriy Umerenkov, Alexandr Nesterov, Vladimir Shaposhnikov, Ruslan Abramov, Nikolay Romanenko, Vladimir Kokh, Marina Kirina, Anton Abrosimov, Dmitry V. Dylov, and Ivan Oseledets. 2025. AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 9880–9889. https://doi.org/10.24963/ijcai.2025/1098

@inproceedings{ijcai2025p1098,
  title     = {AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems},
  author    = {Umerenkov, Dmitriy and Nesterov, Alexandr and Shaposhnikov, Vladimir and Abramov, Ruslan and Romanenko, Nikolay and Kokh, Vladimir and Kirina, Marina and Abrosimov, Anton and Dylov, Dmitry V. and Oseledets, Ivan},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {9880--9889},
  year      = {2025},
  month     = {8},
  note      = {AI and Social Good},
  doi       = {10.24963/ijcai.2025/1098},
  url       = {https://doi.org/10.24963/ijcai.2025/1098},
}

TY  - CPAPER
TI  - AI Diagnostic Assistant (AIDA): A Predictive Model for Diagnoses from Health Records in Clinical Decision Support Systems
AU  - Umerenkov, Dmitriy
AU  - Nesterov, Alexandr
AU  - Shaposhnikov, Vladimir
AU  - Abramov, Ruslan
AU  - Romanenko, Nikolay
AU  - Kokh, Vladimir
AU  - Kirina, Marina
AU  - Abrosimov, Anton
AU  - Dylov, Dmitry V.
AU  - Oseledets, Ivan
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 9880
EP  - 9889
DO  - 10.24963/ijcai.2025/1098
UR  - https://doi.org/10.24963/ijcai.2025/1098
ER  -