Boyko A N, Pliskunova Yu V, Taraskin O V, Paleeva A G, Efimenko I V, Khoroshevsky V F
Pirogov Russian National Research Medical University, Moscow, Russia.
Novartis Pharma, Moscow, Russia.
Zh Nevrol Psikhiatr Im S S Korsakova. 2022;122(7. Vyp. 2):78-83. doi: 10.17116/jnevro202212207278.
To study the needs of patients suffering from multiple sclerosis (MS) in Russia.
The technologies of Big Data analysis and intelligent processing of unstructured information (semantic analysis of natural language texts), developed by Semantic Hub were used. Semantic Hub platform scans digital environment to connect to the sources of interest and to collect data of potential interest (i.e. texts generated by patients and their caregivers, in anonymized form). As the next step, each text is analyzed using natural language understanding technologies to build the knowledge base with aggregated data.
The semantic analysis of natural language texts made it possible to describe virtual population of Russian patients with MS and their caregivers on the Web: age, gender, regions of residence, movements, key Web resources for getting information and communicating with each other, insights about medical care and the quality of life of patients with MS.
In addition to doctors' recommendations, today the patient can get information from various sources, including other patients with MS. This trend requires attention of medical community: it is necessary to help patients get reliable information about the disease, and methods of therapy. Doctor-to-patient communication on the Web should be widely discussed to develop effective and ethical approaches.
研究俄罗斯多发性硬化症（MS）患者的需求。
使用了语义中心开发的大数据分析和非结构化信息智能处理技术（自然语言文本的语义分析）。语义中心平台扫描数字环境，以连接到感兴趣的来源并收集潜在感兴趣的数据（即患者及其护理人员以匿名形式生成的文本）。下一步，使用自然语言理解技术对每个文本进行分析，以建立包含汇总数据的知识库。
自然语言文本的语义分析使得能够描述俄罗斯MS患者及其护理人员在网络上的虚拟群体：年龄、性别、居住地区、活动、获取信息和相互交流的关键网络资源、对医疗护理的见解以及MS患者的生活质量。
除了医生的建议外，如今患者还可以从各种来源获取信息，包括其他MS患者。这种趋势需要医学界予以关注：有必要帮助患者获取有关该疾病及治疗方法的可靠信息。应广泛讨论网络上的医患沟通，以制定有效且符合道德规范的方法。
