Vector-borne diseases (VBDs) are a kind of infection caused through the transmission of vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks, mosquitoes, triatomine bugs, blackflies, and sandflies. If these diseases are not properly treated within a reasonable time frame, the mortality rate may rise. In this work, we propose a set of ontologies that will help in the diagnosis and treatment of vector-borne diseases. For developing VBD's ontology, electronic health records taken from the Indian Health Records website, text data generated from Indian government medical mobile applications, and doctors' prescribed handwritten notes of patients are used as input. This data is then converted into correct text using Optical Character Recognition (OCR) and a spelling checker after pre-processing. Natural Language Processing (NLP) is applied for entity extraction from text data for making Resource Description Framework (RDF) medical data with the help of the Patient Clinical Data (PCD) ontology. Afterwards, Basic Formal Ontology (BFO), National Vector Borne Disease Control Program (NVBDCP) guidelines, and RDF medical data are used to develop ontologies for VBDs, and Semantic Web Rule Language (SWRL) rules are applied for diagnosis and treatment. The developed ontology helps in the construction of decision support systems (DSS) for the NVBDCP to control these diseases.
翻译:病媒传染疾病(VBDs)是通过感染寄生虫、细菌和病毒,如滴虫、蚊子、三甲虫虫、黑蝇和沙蝇的咬咬咬、细菌和病毒的咬咬咬而传播的病媒,如滴虫、蚊虫、蚊虫、三甲虫虫虫虫、黑蝇和沙蝇等,造成一种感染。如果这些疾病在合理的时间范围内得不到适当治疗,死亡率可能会上升。在这项工作中,我们提出一套有助于诊断和治疗病媒传染疾病的疾病的方法。为了发展VBD的肿瘤学,从印度健康记录网站上的电子健康记录、印度政府医疗移动应用的文本数据以及医生规定的病人手写笔记被用作投入。然后,将这些数据转换成正确的文本,使用光性特征识别(OCRCR)和拼写检查器进行预处理。自然语言处理(NLPP)用于实体从文本数据提取数据,以编制《资源说明框架》医疗系统(PCDD)的临床数据(PDRDFDR) 基本正式的肿瘤(BFMDF) 国家病理病理病理病理病理病理学管理准则和SLDUDFS 用于VDFDL 语言病理学的S的S 规则的制定过程。