Gogoberidze Y T, Klassen V I, Natenzon M Y, Prosvirkin I A, Vladzimirsky A V, Sharova D E, Zinchenko V V
Senior Development Engineer; PhthisisBioMed LLC, 135 Karla Marksa St., Chistopol, Republic of Tatarstan, 422980, Russia.
Professor, General Director; RK Vector JSC, 135 Karla Marksa St., Chistopol, Republic of Tatarstan, 422980, Russia; Board Chairman; PhthisisBioMed LLC, 135 Karla Marksa St., Chistopol, Republic of Tatarstan, 422980, Russia.
Sovrem Tekhnologii Med. 2023;15(4):5-19. doi: 10.17691/stm2023.15.4.01. Epub 2023 Jul 28.
The scope of diagnostic medical examinations increases from year to year causing a reasonable desire to develop and implement new technologies to diagnostics and medical data analysis. Artificial intelligence (AI) algorithms became one of the most promising solutions to this problem and proved themselves in the course of mass practical application. During the three-year Moscow experiment started in 2020, the possibility was achieved to develop methodologies of AI use and to successfully implement it into the regional level healthcare system. In this article, the authors share their experience in developing a medical AI service using the example of PhthisisBioMed AI service and the results of its application in real clinical activities environment. This AI service has shown its quality and reliability confirmed by technological monitoring. Clinical trials of PhthisisBioMed AI service were conducted on a specially prepared verified data set (n=1536) considering epidemiological indicators of the thoracic organs major diseases prevalence. The mean sensitivity of the service was 0.975 (95% CI: 0.966-0.984). PhthisisBioMed medical AI service is registered as a medical device (medical device registration certificate No.RZN 2022/17406 dated May 31, 2022) and is actively used in the Russian Federation as a diagnostic tool to reduce the burden on radiologists and to accelerate the process of medical report obtaining.
诊断性医学检查的范围逐年扩大,这引发了开发和应用新技术进行诊断及医学数据分析的合理需求。人工智能(AI)算法成为解决这一问题最具前景的方案之一,并在大规模实际应用过程中得到了验证。在始于2020年的为期三年的莫斯科实验中,实现了开发人工智能使用方法并将其成功应用于地区级医疗保健系统的可能性。在本文中,作者以肺结核生物医学人工智能服务为例,分享了他们开发医疗人工智能服务的经验及其在实际临床活动环境中的应用结果。该人工智能服务已通过技术监测证明了其质量和可靠性。肺结核生物医学人工智能服务的临床试验是在一个经过特别准备的验证数据集(n = 1536)上进行的,该数据集考虑了胸部器官主要疾病患病率的流行病学指标。该服务的平均敏感度为0.975(95%置信区间:0.966 - 0.984)。肺结核生物医学医疗人工智能服务已注册为医疗器械(医疗器械注册证书编号:RZN 2022/17406,日期为2022年5月31日),并在俄罗斯联邦作为一种诊断工具被积极使用,以减轻放射科医生的负担并加快获取医学报告的过程。