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21ISI ЖУРНАЛ КАЗАХСТАНСКО-РОССИЙСКОГО МЕДИЦИНСКОГО УНИВЕРСИТЕТА
UCD: 616.028-78;615-89 MPHTM: 76.75.02.
CHAT-BOTS IN EARLY DETECTION OF COVID-19
I. Vikhrov, Sh. Ashirbayev, *M. Qodirova
Tashkent Pediatric Medical Institute, Uzbekistan, Tashkent
Summary
A brief overview of this example is provided in Uzbekistan and other countries. It also provides statistics on the early disease detection program and differential diagnosis with other diseases.
The authors give a brief overview of how chatbots created in other countries work and how effective they are. The topic of chatbots is very important in the healthcare industry, which means that doctors and nurses who work directly with patients are freed from some of the routine functions of their work. The idea of using chat bots is as follows: to make information about the current situation more reliable; exclude the congestion of people in medical institutions; optimize drug prescriptions and facilitate access to health care.
The presented study covers the period from June to October 2021. The chatbot was developed by the authors to help differentiate the Covid-19, flu and ARVI (acute respiratory viral infection). The copyright certificate was received at the Intellectual Property Agency of the Republic of Uzbekistan.
In almost all developed countries, especially in the field of medicine, artificial intelligence based on digital technologies is actively promoted and widely used. The analysis shows that the USA, many countries in Europe and India have the largest number of chatbot users.
The use of chatbots also provides the community with information on self-protection, disease prevention, and first aid measures.
Key words: covid-19, chat-bot, artificial intelligence.
Introduction. As of March 2021, the World Health Organization estimates that nearly 120 million cases of COVID-19 have resulted in more than 2.5 million deaths worldwide [1]. During the Covid-19 pandemic around the world, new research was created in all areas, including in the healthcare system. It's hard to imagine a world of news without modern technology. Additionally, during the Co-vid-19 pandemic in Uzbekistan, a number of studies were conducted in the field of methodological manuals, online surveys, call centers, mobile applications. It is no secret that despite the research, this epidemiological process is still going on, which has a significant negative impact on its economic, social and health sectors. Despite the advice and information provided by the media during the pandemic, the number of polls among the population has increased. In fact, he tries finding complete information by searching on social media in order to get clear answers to the questions that interest him. This will enable the development of measures to meet the information needs of the population and the introduction of digital technologies in the healthcare system [2]. The Covid-19 Checker chat-bot was created in 2021 to manage the epidemiological situation, in accordance with the recommendations and guidelines of the World Health Organization.
Materials and research methods. During the global pandemic, the use of chatbots increased significantly. Data on the use of chatbots in the healthcare system have been researched. These terms have been reviewed and analyzed in professional journal articles, including PubMed, Springer Link, Journal of Medical Internet Research, and Google Scholar. The study included only articles published in 2019-2021. From our research on the 10 most used chatbots, we analyzed that the most chatbots were used in Europe and the USA.
In Uzbekistan, the COVID-19 Checker web application was used. The survey was conducted from July to October 2021.
Based on guidelines from the Italian healthcare system, Covid-19 worked on an anonymous survey called "Support for Surveys" during the pandemic. Query Support (QS) software is designed as a web-based algorithm [3]. Sorting out users with COVID-19 - Recommendations are made for screening those who have had contact with patients with confirmed symptoms or confirmed COVID-19 virus and taking appropriate action. Including anonymous access to the system is open to any user. continuous communication is based on a chat interface [4].
The algorithm was based on the 2009 Patient Selection for Nurses (HBS) program, which was developed around the world when the H1N1 virus was detected [5]. In this program, a coordinated state-wide HBS system called MN Flu Line (Minnesota Flu Line) was created to address the following objectives: (1) to provide accurate information -to send consistent messages and assistance, including the use of antiviral drugs reducing public confusion through;
(2) reducing the spread of the disease by reducing the number of patients who accumulate in health facilities;
(3) reduction of medical indications in HCS to ensure that other priority medical needs are met; and (4) meeting the needs of uninsured or uninsured patients and patients who do not have easy access to health care [6].
Another study, using the concept of artificial intelligence created in a pandemic environment in Boston, USA, introduced the use of artificial intelligence to optimize claims and complaints in the "Nurse Helpline" only chat bot. The introduction of artificial intelligence to remotely perform tasks performed individually by clinical staff is an important step in the health care system. The Nurse
Helpline online chat bot provides advice on patient management, hospitalization of medium and severe patients, staying at home, and self-protection for those who come in contact with a virus-confirmed patient. The chat was used effectively by citizens and medical staff. The use of this chatbot for early diagnosis of the disease and to limit the chain of transmission of the disease received a 58% positive result [7].
At the beginning of the COVID-19 pandemic, the Copenhagen Emergency Medical Services (CEMS) developed a digital diagnostic "See a Doctor" chatbot to assess signs of infection. Launched in the Danish capital region. One week later, the device was introduced nationwide in Denmark and was used more than 90,000 times in the first week and almost 150,000 times in the second week. The chatbot was provided for two different purposes: (a) to assist isolated citizens in assessing whether their symptoms were potentially associated with COVID-19 and to advise them on when and where to seek additional medical care; and (b) reducing the number of calls to health hotlines [8].
These chat citizens and Research has also been conducted in India, which ranks third in the world in terms of Covid-19 incidence. Coronavirus symptom testing Chatbot "AVA" Chatbot developed under the guidance of WHO and the Indian Ministry of Health and Family Welfare. This Chatbot developed an app based on population, age, gender, whether or not they were communicating, and a number of important surveys [9].
Published in the Journal of Experimental Psychology on October 28, 2021, French scientists have developed a Chatbot that offers tailored answers to questions posed by curious or hesitant people and demonstrated its effectiveness. Vaccination hesitation is one of the key challenges in the fight against the COVID-19 pandemic. Previous research has shown that mass communication through short messages broadcast on television or radio is not an effective means of persuad-
ing hesitant. The team tested their Chatbot with 338 people. After a few minutes of chatting with Chatbot, the number of participants who expressed a positive opinion on the vaccine increased by 37%. After using Chatbot, people became more prone to vaccination, and the idea of vaccine rejection decreased by 20%. Additionally, this Chatbot is regularly updated with information about the new vaccine [10].
In Uzbekistan, in line with the world, a survey of the web application COVID-19 Checker has been developed. The survey was conducted from July to October 2021. The survey was conducted online via mobile phone, answering questions from participants about gender, age, whether or not they had been vaccinated, symptoms, and contact with other people.
A study conducted in Uzbekistan in this area, the Covid-19 checker bot developed by the Tashkent Pediatric Institute, involved 332 respondents, men and women aged 20-60 years and older [11].
Another was the creation of the Covid-19 Preliminary Test website, developed by the Ministry of Health. Unlike the Covid-19 checker bot, this online survey includes a few additional questions. For example: there are chronic diseases; whether or not they have been on a trip to a foreign country [12].
A total of 75,557 participants took part in the Italian "Survey Support" Chatbot. Of those, 65,207 were diagnosed with the flu and 19,062 had the Covid-19 virus. Of the users, 65,207 had symptoms but no PSR confirmed, as well as 8,692 participants who had contact with a patient with COVID-19 status [3].
A total of 2,618,862 participants reported potential symptoms of COVID-19 in the American-made online mobile app Nurse Helpline. Among 18,401 people who tested SARS-CoV-2, the proportion of participants who reported loss of smell and taste was positive (4,668 of 7,178 people; 65.03%) with a negative test, which was higher than that of the positive. 805 753- The partici-
Table 1. COVID-19, Separation of signs and symptoms of cold and flu.
Symptom or indicator Covid-19 Common cold Influenza
Temperature 150 20 80
Dry cough 150 20 75
Loss of smell or taste 150 0 15
Fatigue 150 10 10
Dyspnea 150 0 0
Joint pain 50 60 80
Diarrhea 50 0 80
Sore throat 50 70 10
Headache 30 10 80
Nausea and vomiting 30 0 0
Skin rashes 20 0 5
Rhinorrhoea 10 80 5
Sneezing 0 80 0
Redness and burning in the eyes (conjunctivitis) 20 10 10
Pain in the eyes 0 20 70
Abdominal pain 30 60 10
May - August 0 0 0
September - January 0 0 0
February - April 0 0 0
Contact with an infected person 200 10 10
в
ЖУРНАЛ КАЗАХСТАНСКО-РОССИИСКОГО МЕДИЦИНСКОГО УНИВЕРСИТЕТА
V
pant estimated that COVID-19 may be present, of which 140,312 (17.42%) confirmed Covid-19 virus [7].
Results. The research conducted by the staff of the Innovation Center of the Tashkent Pediatric Medical Institute covers the period up to June-October 2021.COVID-19_ CHECKER as part of our research, Chatbot was developed to help Chatbot users make a differential diagnosis between cold and flu. We analyzed COVID-19, the most common symptoms of cold and flu, and took into account some signs and indications. Table 1.-1 shows the recommended distribution of signs and symptoms to provide information needed to distribute COVID-19, the likelihood of influenza and influenza infection, considering the seasonality and epide-miological situation.
Based on epidemiological situation, symptoms such as COVID-19 pentad's, fever, dry cough, loss of smell or taste, shortness of breath, and fatigue were given maximum scores. Vaccinations of users were also taken into account, which affected reducing the likelihood of contracting COVID-19.
Further, recommendations were developed, which were based on the percentage of the respondent's likelihood of COVID-19. A copyright certificate was obtained for the developed program at the Agency for Intellectual Property of the Republic of Uzbekistan (certificate No. DGU12138 dated 07/09/2021).
In total, 332 people took part in the online survey via CO-VID-19_CHECKER Chatbot between July and October 2021. Thus, the distribution of signs and symptoms is as follows.
200 150 100 50
GENDER 174
158
DISEASE 153
54
57
0
Female Male COVID 19 Flu Cold No illness
Figure 1. Distribution by sex and disease according to the Chatbot COVID-19 CHECKER.
Figure 2. The distribution of symptoms and signs of COVID-19 CHECKER Chatbot.
According to the results of the Chatbot operation, the following data were obtained, out of 332 participants, 174 were women and 158 were men. Of these, COVID-19 - 153 respondents, flu - 68, colds - 54 and 57 participants are not sick.
Figure 2. In this figure, the presence and absence of symptoms and signs are given. Among these indicators, the most common symptom in participants was weakness - 208, while in 124 participants it was not observed. Another 294 participants with skin rashes denied this sign. Another of the most common symptoms was headache in 160 participants, and no symptoms of sore throat in 206 participants.
Conclusion. The results show that at a time when the number of cases with Covid-19 is increasing, it is necessary to further increase the number of high-tech bots being developed in the
healthcare system and ensure that they are perfectly developed and widely used in practice. we can observe the need to put.
In almost all developed countries, especially in the field of medicine, artificial intelligence based on digital technologies has been promoted and widely used. The need for this trend is growing. Research and analysis show that the United States, Europe, and India have the highest number of Chatbot users.
Most countries' digital responses include a combination of big data analysis, integration of national health insurance databases, tracking travel history from person location databases, code scanning, and online person reporting. What is lacking in the COVID-19 pandemic around the world is an integrated approach to digital health governance. Bulk surveillance and contact tracing that collect personal
data should not be used by government agencies without public scrutiny, but should be associated with contactless anonymized digital health technologies.
In the Republic of Uzbekistan, digital solutions for tracking contacts with AI, including chat bots, are still under development. Although a number of options for mobile COVID-19 contact tracing applications have been proposed, they have not been able to find their place in the official anti-epidemic measures of the Uzbek government to combat the spread of infection. Nevertheless, the effective possibilities of such digital solutions for the epidemiological prevention of infection at the level of communities, cities and countries are beyond doubt.
In conclusion, note that digital chatbots using AI can become a tool in the fight against COVID-19 and similar pandemics. However, from the above literature review of the current state of the art, note that AI systems are still in preliminary stages and it will take time before results are seen. Very few of the examples and models of digital Chatbot solutions we've reviewed have operational maturity at this stage.
References:
1. WHO Coronavirus (COVID-19) Dashboard. World Health Organization. URL: https://covid19.who.int [accessed 2021-08-01].
2. Rovetta A., Bhagavat hula A.S. COVID-19-Related Web Search behavior and Infodemic Attitudes in Italy: Endemiological Study. JMIR Public Health Surveille 2020 May 05; 6 (2): e19374 [FREE Full text] [doi: 10.2196 / 19374] [Medline: 32338613] Haase CB, Bearman M., Brodersen J., Hoeyer K., Risor T. 'You should see a doctor ', said the robot: Reflections on a digital diagnostic device in a pandemic age. Scand J. Public Health 2021 Feb; 49 (1): 33-36 [FREE Full text] [doi: 10.1177 / 1403494820980268] [Medline: 33339468]
3. Cosa sapere su test, tracciamento, quarantena. Minister of the Salute. URL: https://www.salute.gov.it/portale/ nuovocoronavirus/dettaglioFaqNuovoCoronavirus.jsp? Lingua = italiano & id = 244 [accessed 2021-08-01].
4. Paginemediche: the piattaforma che connette medici e pazienti. URL: https://www.paginemediche.it/ [accessed 2021-08-01].
5. Hautz W.E., Exadaktylos A., Sauter T.C. Online forward triage during the COVID-19 outbreak. Emerg Med J 2020 Dec 11: 1 [FREE Full text] [doi: 10.1136 / emermed-2020-209792] [Medline: 33310732].
6. Spaulding A.B., Radi D., Macleod H., Lynfield R., Larson M., Hyduke T., et al. Design and implementation of a statewide influenza nurse triage line in response to pandemic H1N1 influenza. Public Health Rep 2012; 127 (5): 532-540 [FREE Full text] [doi: 10.1177 / 003335491212700509] [Medline: 22942472].
7. Lai L., Wittbold K.A., Dadabhoy F.Z., Sato R., Landman A.B., Schwamm L.H., et al. Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic. Healthc (Amst) 2020 Dec; 8 (4): 100493 [FREE Full text] [doi: 10.1016 / j.hjdsi. 2020.100493] [Medline: 33129176].
8. Haase C.B., Bearman M., Brodersen J., Hoeyer K., Risor T. 'You should see a doctor', said the robot: Reflections on a digital diagnostic device in a pandemic age. Scand J Public Health 2021 Feb; 49 (1): 33-36 [FREE Full text] [doi: 10.1177 / 1403494820980268] [Medline: 33339468].
9. Healify group, India, New Delhi, 'AVA" chat bot Heallify - Coronavirus Symptoms Checker Tool COVID-19 is developed based on the guidelines of WHO and Ministry of Health and Family.
10. https://www.cnrs.fr/en/chatbot-addressing-covid-19-vaccine-hesitancyChatbot for addressing COVID-19 vaccine hesitancy, Journal of Experimental Psychology: Applied (October 28, 2021).
11. https://tashpmi.uz/podrazdeleniya-instituta/czentry/ innovaczionnyj-czentr/https://tashpmi.uz/uz/institut-bolimlari/markazlar/innovatsiya-markazi/@covid19_ checkerbot.
12. Covid-19_checker bot https://coronavir/.
СОУГО-19 КЕЗЩДЕ ЕРТЕ АНЬЩТАЛГАН ЧАТ-БОТТАР
И. Вихров, Ш. Аширбаев, *М. Кодирова
Ташкент педиатриялыц медицинальщ институты, бзбекстан, Ташкент ц.
ТYЙiндi
Осы зерттеудщ цысцаша шолуы бзбекстанда жэне басца елдерде Covid-19 пандемиясы кезшде цифрлыц технологиялар-ды цолдана отырып, мобильдi чат-бот цосымшасынын цурылуы мен жумысына талдау жасайды. Сондай-ац, ауруды ерте аныцтау жэне басца аурулармен дифференциалды диагноз цою багдарламасы бойынша статистика усынылады.
Авторлар басца елдерде жасалган чатботтар цалай жумыс ктейпш жэне олардыц цаншалыцты тиiмдi екендш тура-лы цысцаша шолу жасайды. Чатботтар тацырыбы Денсаулыц сацтау саласында ете мацызды, ягни пациенттермен ткелей жумыс ктейтш дэртерлер мен медбикелер ез жумысынын кейбiр эдеттеп функцияларынан босатылады. Чат-боттарды пайдалану идеясы мынадай: осы жагдай туралы ацпаратты шынайы ету; медициналыц мекемелерде адамдардын жиналуын болдырмау; дэршк тагайындауларды онтайландыру жэне медициналыц кемектщ цолжетiмдiлiгiн женiлдету.
¥сынылган зерттеу 2021 жылгы маусымнан цазанга дейiнгi кезендi цамтиды. Чатботты авторлар тумау мен суыц тию арасында дифференциалды диагноз Covid-19, ЖРВИ (жiтi респираторлыц вирустыц инфекция) цоюга кемектесу Yшiн жасаган. Т^ зияткерлiк меншiк агенттiгiнен авторлыц куэлiк алынды.
Барлыц дерлiк дамыган елдерде, эсiресе медицина саласында, сандыц технологияларга негiзделген жасанды интеллект белсендi тYPде дамып келедi жэне кещнен цолданылады. Талдау керсеткендей, А^Ш, Еуропанын кептеген елдерi жэне Yндiстан чат-боттарды пайдаланушылардын ен кеп санына ие.
Чатботты пайдалану цогамга езiн-езi цоргау, аурудын алдын-алу жэне алгашцы кемек шаралары туралы ацпарат бередi.
Ктт свздер: covid-19, чат-бот, жасанды интеллект.
ЖУРНАЛ КАЗАХСТАНСКО-РОССИЙСКОГО МЕДИЦИНСКОГО УНИВЕРСИТЕТА ЧАТ-БОТЫ ПРИ РАННЕМ ОБНАРУЖЕНИИ COVID-19
И. Вихров, Ш. Аширбаев, *М. Кодирова
Ташкентский педиатрический медицинский институт, Узбекистан, г. Ташкент
Аннотация
В кратком обзоре этого исследования представлен анализ создания и работы мобильного приложения чат-бота с использованием цифровых технологий во время пандемии Covid-19 в Узбекистане и других странах. Также предоставляется статистика по программе раннего обнаружения болезни и дифференциального диагноза с другими заболеваниями.
Авторы делают краткий обзор того, как работают чат-боты, созданные в других странах, и насколько они эффективны. Тема чат-ботов очень важна в сфере здравоохранения, а это значит, что врачи и медсестры, которые работают непосредственно с пациентами, освобождаются от некоторых рутинных функций своей работы. Идея использования чат-ботов заключается в следующем: сделать информацию о настоящей ситуации более достоверной; исключить скопление людей в медицинских учреждениях; оптимизировать лекарственные назначения и облегчить доступность медицинской помощи.
Представленное исследование охватывает период с июня до октября 2021 года. Чат-бот разработан авторами, чтобы помочь проводить дифференциальную диагностику между Covid-19, гриппом и ОРВИ (острая респираторная вирусная инфекция). Получено авторское свидетельство в Агентстве интеллектуальной собственности РУ.
Практически во всех развитых странах, особенно в области медицины, искусственный интеллект, основанный на цифровых технологиях, активно продвигается и широко используется. Анализ показывает, что США, многие страны Европы и Индия имеют наибольшее количество пользователей чат-ботов.
Использование чат-ботов также предоставляет сообществу информацию о самозащите, профилактике заболеваний и мерах первой помощи.
Ключевые слова: covid-19, чат-бот, искусственный интеллект.
УДК: 614.446.33 МРНТИ: 76.29.50.
МОНИТОРИНГ ТЕЧЕНИЯ COVID-19 У ДЕТЕЙ В УСЛОВИЯХ
ПОЛИКЛИНИКИ
Г.Е. Абдрахманова, Е.Н. Шорина, С.К. Шабдарова, А.А. Куандыкова, *Э.М. Тораханов, К.К. CepiK, А.А. Сапарова, Д.А. Кулиманова, А.Б. Байгуатова
НУО «Казахстанско-Российский медицинский университет», Казахстан, г. Алматы
Аннотация
Авторами представлены исследования, посвященные особенностям клинического течения новой коронавирусной инфекции у педиатрических пациентов. В основу статьи положен анализ зарубежных публикаций в рецензируемых журналах и исследования пациентов детского возраста, проведенные на амбулаторно-поликлиническом уровне. Новый коронавирус (SARS-CoV-2) вызывает заболевание у детей всех возрастных групп, начиная с новорожденных, которое протекает в более легкой форме. Установлено, что дети значительно легче переносят СОУ[Э-19. Исследователи отмечают преобладание у детей бессимптомных и легких форм заболевания. Показано, что СОУ[Э-19 у детей имеет существенно благоприятный исход. Особое внимание авторы обращают на то, что именно дети как категория пациентов с наиболее высоким уровнем бессимптомного и легкого течения заболевания составляют основной трансмиссивный потенциал для продолжения пандемии.
Ключевые слова: дети, новая коронавирусная инфекция, пандемия, COVЮ-19.
Актуальность. 11 марта 2020 г. ВОЗ объявила о начале пандемии COVID-19 (Coronavirus disease 2019) [1]. В настоящее время в мире растет число людей инфицированных коронавирусом SARS-CoV-2, вызывающим COVID-19. Так как ранее такой пандемии не было, необходимо изучение особенностей распространения и клинической картины, в частности в детской популяции.
Цель — на основании результатов работы ГКП №29 г. Алматы, в условиях пандемии проанализировать
особенности течения и клинической картины короно-вирусной инфекции у пациентов детского возраста.
Материалы и методы исследования. Наше исследование проводилось на основе ГКП на ПХВ ГП №29 г.Алматы где была проведена полная реорганизация внутреннего устройства поликлиники в условиях пандемии СОУ[Э-19 по выявлению и оказанию специализированной медицинской помощи больным, которые инфициро-ванны SARS-CoV-2. Весь персонал поликлиники прошел обучение по выявлению и сортировке пациентов с сим-
