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Artificial Intelligence Applications in Emergency Toxicology: Advancements and Challenges
Lorraine Pei Xian Yong1,2, Joshua Yi Min Tung3, Nicole Mun Teng Cheung1,2
1Urgent Care Centre, Alexandra Hospital, Singapore, Singapore.
Journal of Medical Internet Research
|August 22, 2025
Summary
Artificial intelligence (AI) shows promise in emergency toxicology for faster diagnoses and better patient outcomes. However, challenges like data quality and implementation must be addressed for widespread clinical use.
Area of Science:
- Emergency medicine
- Toxicology
- Artificial Intelligence
Background:
- Emergency toxicology demands rapid decision-making for acute poisonings.
- Time and resource constraints challenge traditional diagnostic and treatment methods.
- Artificial intelligence (AI) offers potential in emergency medicine, but its role in toxicology is underexplored.
Purpose of the Study:
- To provide perspectives on AI applications in emergency toxicology.
- To highlight key advancements, challenges, and future directions for AI in this field.
Main Methods:
- This viewpoint discusses current and potential AI applications.
- It reviews existing literature and expert opinions on AI in emergency toxicology.
Main Results:
- AI demonstrates significant potential in improving toxicological predictions.
- Key challenges include data quality, regulatory concerns, and implementation barriers.
Conclusions:
- Further research, regulatory frameworks, and integration strategies are essential.
- Effective and ethical implementation of AI in clinical practice requires addressing identified hurdles.
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