Ignite Creation Date:
2024-06-16 @ 11:51 AM
Last Modification Date:
2024-10-26 @ 3:32 PM
Study NCT ID:
NCT06456866
Status:
RECRUITING
Last Update Posted:
2024-06-13
First Post:
2024-06-08
Brief Title:
Assessing the Accuracy of ChatGPT-4 in Interpreting Arterial Blood Gas Results
Sponsor:
Kanuni Sultan Suleyman Training and Research Hospital
Organization:
Kanuni Sultan Suleyman Training and Research Hospital
Study Overview
Official Title:
Assessing the Accuracy of ChatGPT-4 in Interpreting Arterial Blood Gas Results
Status:
RECRUITING
Status Verified Date:
2024-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Assessment of Acidosis and Alkalosis Evaluation of Hypoxemia and Hyperoxemia Evaluation of Hemoglobin Parameters Assessment of Electrolytes Evaluation of Metabolic Parameters Glucose Lactate Bilirubin
Detailed Description:
Model Training
The collected data will be used to train the artificial intelligence model Utilizing the deep learning infrastructure provided by ChatGPT Plus our model will be optimized to produce highly accurate results in interpreting blood gases
During the training process our model will be taught to interpret various blood gas samples including assessments of acidosis-alkalosis hypoxemia-hyperoxemia hemoglobin electrolytes and metabolic parameters
Model Testing and Validation
The trained model will be tested on previously unseen test datasets to evaluate its performance This step is crucial for understanding how the model will perform in real-world scenarios
The accuracy of the model will be assessed by comparing its interpretations with feedback provided by expert anesthesiologists
Furthermore to comprehensively evaluate ChatGPTs effectiveness in this domain the daily arterial blood gas results obtained in the intensive care unit will be submitted to ChatGPT for interpretation The same questions will be posed and the responses will be evaluated by an anesthesiology and reanimation specialist These questions will be asked to the model
Assessment of Acidosis and Alkalosis Evaluation of Hypoxemia and Hyperoxemia Evaluation of Hemoglobin Parameters Assessment of Electrolytes Evaluation of Metabolic Parameters Glucose Lactate Bilirubin
The collected data will be used to train the artificial intelligence model Utilizing the deep learning infrastructure provided by ChatGPT Plus our model will be optimized to produce highly accurate results in interpreting blood gases
During the training process our model will be taught to interpret various blood gas samples including assessments of acidosis-alkalosis hypoxemia-hyperoxemia hemoglobin electrolytes and metabolic parameters
Model Testing and Validation
The trained model will be tested on previously unseen test datasets to evaluate its performance This step is crucial for understanding how the model will perform in real-world scenarios
The accuracy of the model will be assessed by comparing its interpretations with feedback provided by expert anesthesiologists
Furthermore to comprehensively evaluate ChatGPTs effectiveness in this domain the daily arterial blood gas results obtained in the intensive care unit will be submitted to ChatGPT for interpretation The same questions will be posed and the responses will be evaluated by an anesthesiology and reanimation specialist These questions will be asked to the model
Assessment of Acidosis and Alkalosis Evaluation of Hypoxemia and Hyperoxemia Evaluation of Hemoglobin Parameters Assessment of Electrolytes Evaluation of Metabolic Parameters Glucose Lactate Bilirubin
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None