SberHealth's GigaChat-powered artificial intelligence assistant has demonstrated a diagnostic accuracy rate of 93% during recent tests conducted by the Artificial Intelligence Research Institute (AIRI).
The experiment involved the AI healthcare assistant, which is based on the GigaChat neural network model, diagnosing 30 real clinical cases that were randomly selected from the New England Journal of Medicine. These cases varied in complexity, and the testing methodology used was similar to an experiment conducted by Microsoft to verify its own AI diagnostic orchestrator, MAI-DxO.
According to AIRI, the SberHealth system established correct diagnoses in 28 out of 30 cases, while a comparable foreign solution recorded an 85% accuracy rate.
The AI assistant operated with limited initial data, receiving only the patient's gender, age and symptoms before interacting through simulated doctor-patient dialogues. It followed a sequence of requesting additional clinical tests, imaging, or consultation information as needed to make diagnoses. The median number of dialogue turns between the AI and the simulated patient was three, indicating a relatively high speed of decision-making.
Sergey Zhdanov, Director of the Healthcare Industry Centre at Sberbank, said:
"The experiment demonstrated that our technology is not only competitive but also sets new standards in medical diagnostics worldwide. We observe how multi-agent architecture speeds up and enhances the diagnostic process. It's particularly important that the system exhibits flexibility: it revises hypotheses, requests additional data, and even responds to the emotional presentation of clinical scenarios. In the future, this opens up opportunities for interdisciplinary care teams, with AI serving as a reliable assistant to physicians."
During the experiment, each clinical case was labelled by level of difficulty. The AI system was able to successfully identify and diagnose several rare conditions, including Whipple disease, which it recognised in one step, aceruloplasminemia, identified in six moves, and rasburicase-induced methemoglobinemia.
The assistant's performance was characterised by several features, according to researchers. It typically completed diagnoses in three moves, deployed logical reasoning, and handled both rare and complex pathologies. The system was also noted for its ability to blend clinical accuracy with a dialogue logic that could adapt effectively to different presentation styles, which included effectively responding to emotional cues in simulated scenarios.
Ivan Oseledets, Chief Executive Officer of AIRI, commented:
"Today, multi-agent systems are capable of confidently identifying rare, masked pathologies that go beyond typical emergency department algorithms. Can a medical AI assistant adjust its hypothesis in time, discarding the most probable but incorrect pathway? The AI assistant proved it could, doing so faster than anticipated by a seasoned observer with 15 years of medical experience."
The researchers at AIRI described the experiment as exploratory and indicated that further development is planned. They have proposed expanding the sample size by incorporating additional cases from other medical journals to investigate the capabilities of the assistant more widely. The system's potential uses were not limited solely to practical medicine but also extended to the area of physician training, where it could offer realistic simulations of complex clinical cases.
The GigaChat-based assistant is a product of cooperation between AIRI and SberMedAI. Since its introduction, it has been piloted in the SberHealth app and has already been used over 160,000 times in real conditions to assist people seeking medical support.
