Emergency consultation system with automatic response software using artificial intelligence. Issue 3 (September 2022)
- Record Type:
- Journal Article
- Title:
- Emergency consultation system with automatic response software using artificial intelligence. Issue 3 (September 2022)
- Main Title:
- Emergency consultation system with automatic response software using artificial intelligence
- Authors:
- Amagasa, Shunsuke
Moriya, Takashi - Abstract:
- Abstract: Introduction: The number of emergency telephone consultations is still increasing, especially among children, and the response has not been able to keep up with the demand. To promote appropriate medical consultation and respond to many consultations, an emergency consultation service using artificial intelligence (AI) was introduced in Saitama Prefecture, Japan in July 2019. Methods: When you enter texts or sentences in the chat-style screen of smartphone or personal computer, the AI recognizing textual entailment will comprehensively identify the gaps in notation, context, etc., and display some possible symptoms. After selecting a symptom, the system will display five urgency levels by answering questions in a flowchart. The number of cases, age distribution, symptoms, and urgency level were extracted from children aged <15 years who used the Saitama AI Emergency Consultation from July 19, 2019 (system start date) to July 19, 2020. Results: The number of people who used the consultation during the period was 25, 896; 8417 (32%) of them were caregivers of children younger than 15 years. Conclusion: The Saitama AI Emergency Consultation service has already been used by caregivers of children. The AI emergency consultation can be potentially developed into a new system at the same level as the telephone consultation system, may improve the convenience of emergency consultations for sudden illness and trauma in children and reduce the burden on emergency medicalAbstract: Introduction: The number of emergency telephone consultations is still increasing, especially among children, and the response has not been able to keep up with the demand. To promote appropriate medical consultation and respond to many consultations, an emergency consultation service using artificial intelligence (AI) was introduced in Saitama Prefecture, Japan in July 2019. Methods: When you enter texts or sentences in the chat-style screen of smartphone or personal computer, the AI recognizing textual entailment will comprehensively identify the gaps in notation, context, etc., and display some possible symptoms. After selecting a symptom, the system will display five urgency levels by answering questions in a flowchart. The number of cases, age distribution, symptoms, and urgency level were extracted from children aged <15 years who used the Saitama AI Emergency Consultation from July 19, 2019 (system start date) to July 19, 2020. Results: The number of people who used the consultation during the period was 25, 896; 8417 (32%) of them were caregivers of children younger than 15 years. Conclusion: The Saitama AI Emergency Consultation service has already been used by caregivers of children. The AI emergency consultation can be potentially developed into a new system at the same level as the telephone consultation system, may improve the convenience of emergency consultations for sudden illness and trauma in children and reduce the burden on emergency medical institutions by promoting appropriate medical consultations. … (more)
- Is Part Of:
- Health policy and technology. Volume 11:Issue 3(2022)
- Journal:
- Health policy and technology
- Issue:
- Volume 11:Issue 3(2022)
- Issue Display:
- Volume 11, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 11
- Issue:
- 3
- Issue Sort Value:
- 2022-0011-0003-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09
- Subjects:
- Emergency medical services -- Pediatric emergency medicine -- Telecommunications -- Smartphone
Medical policy -- Periodicals
Medical technology -- Periodicals
Medical policy
Medical technology
Health Policy -- Periodicals
Biomedical Technology -- Periodicals
Technology Assessment, Biomedical -- Periodicals
Periodicals
362.105 - Journal URLs:
- http://www.sciencedirect.com/science/journal/22118837 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.hlpt.2022.100629 ↗
- Languages:
- English
- ISSNs:
- 2211-8837
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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