Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device
Due to the similarities in symptomatology between COVID-19 and other respiratory infections, diagnosis of these diseases can be complicated. To address this issue, a web application was developed that employs a chatbot and artificial intelligence to detect COVID-19, the common cold, and allergic rhi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/15/7/227 |
| _version_ | 1797589270499688448 |
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| author | Naythan Villafuerte Santiago Manzano Paulina Ayala Marcelo V. García |
| author_facet | Naythan Villafuerte Santiago Manzano Paulina Ayala Marcelo V. García |
| author_sort | Naythan Villafuerte |
| collection | DOAJ |
| description | Due to the similarities in symptomatology between COVID-19 and other respiratory infections, diagnosis of these diseases can be complicated. To address this issue, a web application was developed that employs a chatbot and artificial intelligence to detect COVID-19, the common cold, and allergic rhinitis. The application also integrates an electronic device that connects to the app and measures vital signs such as heart rate, blood oxygen saturation, and body temperature using two ESP8266 microcontrollers. The measured data are displayed on an OLED screen and sent to a Google Cloud server using the MQTT protocol. The AI algorithm accurately determines the respiratory disease that the patient is suffering from, achieving an accuracy rate of 0.91% after the symptomatology is entered. The app includes a user interface that allows patients to view their medical history of consultations with the assistant. The app was developed using HTML, CSS, JavaScript, MySQL, and Bootstrap 5 tools, resulting in a responsive, dynamic, and robust application that is secure for both the user and the server. Overall, this app provides an efficient and reliable way to diagnose respiratory infections using the power of artificial intelligence. |
| first_indexed | 2024-03-11T01:04:08Z |
| format | Article |
| id | doaj.art-e1fc2a0862894c62bf2ec572ed01a6a4 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-11T01:04:08Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-e1fc2a0862894c62bf2ec572ed01a6a42023-11-18T19:26:44ZengMDPI AGFuture Internet1999-59032023-06-0115722710.3390/fi15070227Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring DeviceNaythan Villafuerte0Santiago Manzano1Paulina Ayala2Marcelo V. García3Faculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, EcuadorFaculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, EcuadorFaculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, EcuadorFaculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, EcuadorDue to the similarities in symptomatology between COVID-19 and other respiratory infections, diagnosis of these diseases can be complicated. To address this issue, a web application was developed that employs a chatbot and artificial intelligence to detect COVID-19, the common cold, and allergic rhinitis. The application also integrates an electronic device that connects to the app and measures vital signs such as heart rate, blood oxygen saturation, and body temperature using two ESP8266 microcontrollers. The measured data are displayed on an OLED screen and sent to a Google Cloud server using the MQTT protocol. The AI algorithm accurately determines the respiratory disease that the patient is suffering from, achieving an accuracy rate of 0.91% after the symptomatology is entered. The app includes a user interface that allows patients to view their medical history of consultations with the assistant. The app was developed using HTML, CSS, JavaScript, MySQL, and Bootstrap 5 tools, resulting in a responsive, dynamic, and robust application that is secure for both the user and the server. Overall, this app provides an efficient and reliable way to diagnose respiratory infections using the power of artificial intelligence.https://www.mdpi.com/1999-5903/15/7/227respiratory infectionsartificial intelligencechatbotvital signsweb application |
| spellingShingle | Naythan Villafuerte Santiago Manzano Paulina Ayala Marcelo V. García Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device Future Internet respiratory infections artificial intelligence chatbot vital signs web application |
| title | Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device |
| title_full | Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device |
| title_fullStr | Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device |
| title_full_unstemmed | Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device |
| title_short | Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device |
| title_sort | artificial intelligence in virtual telemedicine triage a respiratory infection diagnosis tool with electronic measuring device |
| topic | respiratory infections artificial intelligence chatbot vital signs web application |
| url | https://www.mdpi.com/1999-5903/15/7/227 |
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