Knowledge Engineering in Construction of Expert Systems on Hereditary Diseases

Кобринский, Б. А.; Демикова, Н. С.; Благосклонов, Н А

doi:10.1007/978-3-030-00617-4_4

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…In the present study, following and Kobrinskii et al (2018), we identified the most frequently repeated words and used unigrams and bigrams (Ghiassi et al, 2013) to understand relevant indicators (Hassan et al, 2020). Textual analysis is based on theories such as Mutual Information (MI) (Datta et al, 2017).…”

Section: Textual Analysismentioning

confidence: 99%

Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content

2023

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The COVID-19 pandemic has caused many entrepreneurs and small and medium enterprises (SMEs) to adapt their business models and business strategies to the consequences caused by the pandemic. In order to identify the main innovations and technologies adopted by SMEs in the pandemic, in the present study, we used a database of 56,941 tweets related to the coronavirus to identify those that contained the hashtag #SMEs. The final sample was analyzed using several data-mining techniques such as sentiment analysis, topic modeling and textual analysis. The theoretical perspectives adopted in the present study were Computer-Aided Text Analysis, User-Generated Content and Natural Language Processing. The results of our analysis helped us to identify 15 topics (7 positive: Free support against Covid-19, Webinars tools, Time Optimizer and efficiency, Business solutions tools, Advisors tools, Software for process support and Back-up tools; 4 negative: Government support, Payment systems, Cybersecurity problems and Customers solutions in Cloud, and and 4 neutral: Social media and e-commerce, Specialized startups software, CRMs and Finance and Big data analysis tools). The results of the present study suggest that SMEs have used a variety of digital tools and strategies to adapt to the changing market conditions brought on by the pandemic, and have been proactive in adopting new technologies to continue to operate and reach customers in a connected era. Future research should be directed towards understanding the long-term effects of these technologies and strategies on entrepreneurial growth and value creation, as well as the sustainability of SMEs in the new era based on data-driven decisions.

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Section: Textual Analysismentioning

confidence: 99%

Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content

2023

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“…Они послужили первичным материалом для формирования базы знаний компьютерной системы. Знания, полученные из литературных источников, структурировались с помощью специально разработанной формы -текстологической карты [15], в которой фиксировался не только факт обнаружения признака, но также срок его манифестации, выраженность и указываемая авторами частота встречаемости для конкретного диагноза. Эти структурированные описания заболеваний, агрегирующие знания из множества источников, были в последующем использованы экспертами при формировании симптомокомплексов, описывающих дифференцируемые ЛБН.…”

Section: материалы и методыunclassified

An artifiсial intelligence computer system for differential diagnosis of lysosomal storage diseases

et al. 2022

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Aim. To improve the efficiency of diagnosis of hereditary lysosomal storage diseases using an intelligent computerbased decision support system.Materials and methods. Descriptions of 35 clinical cases from the literature and depersonalized data of 52 patients from electronic health records were used as material for clinical testing of the computer diagnostic system. Knowledge engineering techniques have been used to extract, structure, and formalize knowledge from texts and experts. Literary sources included online databases and publications (in Russian and English). On this basis, for each clinical form of lysosomal diseases, textological cards were created, the information in which was corrected by experts. Then matrices were formed, including certainty factors (coefficients) for the manifestation, severity, and relevance of signs for each age group (up to 1 year, from 1 to 3 years inclusive, from 4 to 6 years inclusive, 7 years and older). The knowledge base of the expert system was implemented on the ontology network and included a disease model with reference variants of clinical forms. Decision making was carried out using production rules.Results. The expert computer system was developed to support clinical decision-making at the pre-laboratory stage of differential diagnosis of lysosomal storage diseases. The result of its operation was a ranked list of hypotheses, reflecting the degree of their compliance with reference descriptions of clinical disease forms in the knowledge base. Clinical testing was carried out on cases from literary sources and patient data from electronic health records. The criterion for assessing the effectiveness of disease recognition was inclusion of the verified diagnosis in the list of five hypotheses generated by the system. Based on the testing results, the accuracy was 87.4%.Conclusion. The expert system for the diagnosis of hereditary diseases has shown fairly high efficiency at the stage of compiling a differential diagnosis list at the pre-laboratory stage, which allows us to speak about the possibility of its use in clinical practice.

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Fuzzy and Reflection in the Construction of a Medical Expert System

Кобринский¹

2020

JSEA

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The fuzzy of symptoms (including visual images), representations and assessments in medicine correspond to the peculiarities of the picture of the world of the patient and the physician taking into account the influence of reflection. The continuum of intermediate characteristics of the signs creates serious difficulty for their assessment by physicians. Experts' confidence factors not only for linguistic features, but also for visual images can help increase the hypothesis quality in intelligent medical diagnostic systems.

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Knowledge Engineering in Construction of Expert Systems on Hereditary Diseases

Cited by 3 publications

References 18 publications

Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content

Leveraging SMEs technologies adoption in the Covid-19 pandemic: a case study on Twitter-based user-generated content

An artifiсial intelligence computer system for differential diagnosis of lysosomal storage diseases

Fuzzy and Reflection in the Construction of a Medical Expert System

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