Evaluating GPT-4's role in critical patient management in emergency departments.
<h4>Introduction</h4>Recent advancements in artificial intelligence (AI) have introduced tools like ChatGPT-4, capable of interpreting visual data, including ECGs. In our study,we aimed to investigate the effectiveness of GPT-4 in interpreting ECGs and managing patient care in emergency...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0327584 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850065071622848512 |
|---|---|
| author | Yavuz Yiğit Serkan Günay Ahmet Öztürk Baha Alkahlout |
| author_facet | Yavuz Yiğit Serkan Günay Ahmet Öztürk Baha Alkahlout |
| author_sort | Yavuz Yiğit |
| collection | DOAJ |
| description | <h4>Introduction</h4>Recent advancements in artificial intelligence (AI) have introduced tools like ChatGPT-4, capable of interpreting visual data, including ECGs. In our study,we aimed to investigate the effectiveness of GPT-4 in interpreting ECGs and managing patient care in emergency settings.<h4>Methods</h4>Conducted from April to May 2024, this study evaluated GPT-4 using twenty case scenarios sourced from PubMed Central and the OSCE sample question book. These cases, categorized into common and rare scenarios, were analyzed by GPT-4, and its interpretations were reviewed by five experienced emergency medicine specialists. The accuracy of ECG interpretations and subsequent patient management plans were assessed using a structured evaluation framework and critical error identification.<h4>Results</h4>GPT-4 made critical errors in 46% of ECG interpretations in the OSCE group and 50% in the PubMed group. For patient management, critical errors were found in 32% of the OSCE group and 14% of the PubMed group. When ECG evaluations were included in patient management, error rates approached 50%. The inter-rater reliability among evaluators indicated good agreement (ICC = 0.725, F = 3.72, p < 0.001).<h4>Conclusion</h4>While GPT-4 shows promise in specific applications, its current limitations in accurately interpreting ECGs and managing critical patient scenarios render it inappropriate for emergency department use. Future improvements and extensive validations are essential before such AI tools can be reliably deployed in critical healthcare settings. |
| format | Article |
| id | doaj-art-c06af54aaea2441eb6b109afef78776f |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-c06af54aaea2441eb6b109afef78776f2025-08-20T02:49:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01207e032758410.1371/journal.pone.0327584Evaluating GPT-4's role in critical patient management in emergency departments.Yavuz YiğitSerkan GünayAhmet ÖztürkBaha Alkahlout<h4>Introduction</h4>Recent advancements in artificial intelligence (AI) have introduced tools like ChatGPT-4, capable of interpreting visual data, including ECGs. In our study,we aimed to investigate the effectiveness of GPT-4 in interpreting ECGs and managing patient care in emergency settings.<h4>Methods</h4>Conducted from April to May 2024, this study evaluated GPT-4 using twenty case scenarios sourced from PubMed Central and the OSCE sample question book. These cases, categorized into common and rare scenarios, were analyzed by GPT-4, and its interpretations were reviewed by five experienced emergency medicine specialists. The accuracy of ECG interpretations and subsequent patient management plans were assessed using a structured evaluation framework and critical error identification.<h4>Results</h4>GPT-4 made critical errors in 46% of ECG interpretations in the OSCE group and 50% in the PubMed group. For patient management, critical errors were found in 32% of the OSCE group and 14% of the PubMed group. When ECG evaluations were included in patient management, error rates approached 50%. The inter-rater reliability among evaluators indicated good agreement (ICC = 0.725, F = 3.72, p < 0.001).<h4>Conclusion</h4>While GPT-4 shows promise in specific applications, its current limitations in accurately interpreting ECGs and managing critical patient scenarios render it inappropriate for emergency department use. Future improvements and extensive validations are essential before such AI tools can be reliably deployed in critical healthcare settings.https://doi.org/10.1371/journal.pone.0327584 |
| spellingShingle | Yavuz Yiğit Serkan Günay Ahmet Öztürk Baha Alkahlout Evaluating GPT-4's role in critical patient management in emergency departments. PLoS ONE |
| title | Evaluating GPT-4's role in critical patient management in emergency departments. |
| title_full | Evaluating GPT-4's role in critical patient management in emergency departments. |
| title_fullStr | Evaluating GPT-4's role in critical patient management in emergency departments. |
| title_full_unstemmed | Evaluating GPT-4's role in critical patient management in emergency departments. |
| title_short | Evaluating GPT-4's role in critical patient management in emergency departments. |
| title_sort | evaluating gpt 4 s role in critical patient management in emergency departments |
| url | https://doi.org/10.1371/journal.pone.0327584 |
| work_keys_str_mv | AT yavuzyigit evaluatinggpt4sroleincriticalpatientmanagementinemergencydepartments AT serkangunay evaluatinggpt4sroleincriticalpatientmanagementinemergencydepartments AT ahmetozturk evaluatinggpt4sroleincriticalpatientmanagementinemergencydepartments AT bahaalkahlout evaluatinggpt4sroleincriticalpatientmanagementinemergencydepartments |