The Impact of Artificial Intelligence on Emergency Medicine: A Review of Recent Advances
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866910884047093760 |
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| author | Correia, Gustavo Alves, Victor Novais, Paulo |
| author_facet | Correia, Gustavo Alves, Victor Novais, Paulo |
| contents | Artificial Intelligence (AI) is revolutionizing emergency medicine by enhancing diagnostic processes and improving patient outcomes. This article provides a review of the current applications of AI in emergency imaging studies, focusing on the last five years of advancements. AI technologies, particularly machine learning and deep learning, are pivotal in interpreting complex imaging data, offering rapid, accurate diagnoses and potentially surpassing traditional diagnostic methods. Studies highlighted within the article demonstrate AI's capabilities in accurately detecting conditions such as fractures, pneumothorax, and pulmonary diseases from various imaging modalities including X-rays, CT scans, and MRIs. Furthermore, AI's ability to predict clinical outcomes like mechanical ventilation needs illustrates its potential in crisis resource optimization. Despite these advancements, the integration of AI into clinical practice presents challenges such as data privacy, algorithmic bias, and the need for extensive validation across diverse settings. This review underscores the transformative potential of AI in emergency settings, advocating for a future where AI and clinical expertise synergize to elevate patient care standards. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2503_14546 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Impact of Artificial Intelligence on Emergency Medicine: A Review of Recent Advances Correia, Gustavo Alves, Victor Novais, Paulo Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning 68T07 Artificial Intelligence (AI) is revolutionizing emergency medicine by enhancing diagnostic processes and improving patient outcomes. This article provides a review of the current applications of AI in emergency imaging studies, focusing on the last five years of advancements. AI technologies, particularly machine learning and deep learning, are pivotal in interpreting complex imaging data, offering rapid, accurate diagnoses and potentially surpassing traditional diagnostic methods. Studies highlighted within the article demonstrate AI's capabilities in accurately detecting conditions such as fractures, pneumothorax, and pulmonary diseases from various imaging modalities including X-rays, CT scans, and MRIs. Furthermore, AI's ability to predict clinical outcomes like mechanical ventilation needs illustrates its potential in crisis resource optimization. Despite these advancements, the integration of AI into clinical practice presents challenges such as data privacy, algorithmic bias, and the need for extensive validation across diverse settings. This review underscores the transformative potential of AI in emergency settings, advocating for a future where AI and clinical expertise synergize to elevate patient care standards. |
| title | The Impact of Artificial Intelligence on Emergency Medicine: A Review of Recent Advances |
| topic | Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning 68T07 |
| url | https://arxiv.org/abs/2503.14546 |