ORGANIZATION OF DISPENSARY OBSERVATION OF PATIENTS WITH PATHOLOGY OF THE MACULAR RETINA USING ARTIFICIAL INTELLIGENCE SYSTEMS

Aleksandr Chuprov, Irina Pavlovna Bolodurina, A. O. Lositskiy, A. Zhigalov
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Abstract

Background: Despite the mention in the provision of medical care for diseases of the organ of vision, adnexa and orbit about equipping the medical consultative and diagnostic department of the clinic with an optical coherence tomograph, dynamic monitoring of patients with retinal pathology after the start of treatment is most often carried out in a medical ophthalmological center, which reduces accessibility for patients with primary (first identified) morbidity requiring initiation of treatment. The required technology needs to be changed, intensified, incl. using artificial intelligence technologies. Aim: development of methodological foundations for organizational technology for dispensary observation of patients with pathology of the posterior segment of the eye using clinical decision support system (CDSS) based on artificial intelligence. Materials and methods: The assessment of the existing regulatory framework was carried out on the basis of an analysis of the Constitution of the Russian Federation, Federal laws, by-laws, and judicial practice. The creation of a methodology for a structured medical document describing an optical coherence tomography image was carried out using an expert method: a survey of 100 ophthalmologists with the appropriate level of education, incl. additional professional, engaged in the provision of medical services - specialized medical care (treatment) to patients with pathology of the posterior segment of the eye. Results: Using an expert method, 123 binary signs were selected and described to describe the structure of the macular region of the retina in normal and pathological conditions, of which 26 signs were identified that can be interpreted as predictors of worsening of the clinical course of the disease. Conclusion: The developed classifier made it possible to create and train a medical decision support system based on 60,000 medical images, which, as an information service, without making a diagnosis, can change the organization of the dynamic observation process: the formation of patient routing - a primary service using the developed CDSS; if there are signs of deterioration in the clinical picture - routing to a medical ophthalmological center to assess the dynamics, provide specialized services, incl. high-tech medical care.
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利用人工智能系统组织对黄斑视网膜病变患者的诊室观察
背景:尽管在为视力器官、附件和眼眶疾病提供医疗服务时提到要在诊所的医疗咨询和诊断部门配备光学相干断层扫描仪,但在开始治疗后,视网膜病变患者的动态监测通常是在眼科医疗中心进行的,这降低了需要开始治疗的原发性(首次发现的)发病患者的可及性。所需的技术需要改变和加强,包括使用人工智能技术。目的:利用基于人工智能的临床决策支持系统(CDSS),为在诊室观察眼球后段病变患者的组织技术奠定方法论基础。材料和方法:在分析《俄罗斯联邦宪法》、联邦法律、细则和司法实践的基础上,对现有监管框架进行了评估。采用专家方法制定了描述光学相干断层扫描图像的结构化医疗文件方法:对 100 名具有相应教育水平的眼科医生(包括其他专业人员)进行了调查,这些医生从事为眼球后段病变患者提供医疗服务--专业医疗护理(治疗)。结果:采用专家方法,选择并描述了 123 个二元征象,以描述正常和病理情况下视网膜黄斑区的结构,其中 26 个征象可被解释为疾病临床过程恶化的预兆。最后得出结论:该系统作为一种信息服务,在不做出诊断的情况下,可以改变动态观察过程的组织形式:形成病人路由--使用开发的 CDSS 的主要服务;如果临床症状有恶化迹象--路由到眼科医疗中心,以评估动态,提供专业服务,包括高科技医疗护理。
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
44
审稿时长
5 weeks
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