Trial · NCT07888322
Registered outcomes23
Each outcome the trial registered, primary first, in ClinicalTrials.gov's words.
1 to 20 of 23
Download this page as JSON| List | Outcome | Time frame | Description |
|---|---|---|---|
| Primary | Accuracy of the multimodal AI algorithms | Through study completion, an average of 6 months. | Accuracy of the multimodal AI algorithms will be assessed by comparing model predictions with the clinician-reported reference standard for each suspected lesion. Accuracy will be calculated for each applicable cancer type, with bootstrap confidence intervals. |
| Primary | Precision of the multimodal AI algorithms | Through study completion, an average of 6 months. | Precision of the multimodal AI algorithms will be assessed by comparing model predictions with the clinician-reported reference standard for each suspected lesion. Precision will be calculated for each applicable cancer type, with bootstrap confidence intervals. |
| Primary | F1-score of the multimodal AI algorithms | Through study completion, an average of 6 months. | F1-score will be calculated to assess the classification performance of the multimodal AI algorithms against the clinician-reported reference standard for each suspected lesion. F1-score will be calculated for each applicable cancer type, with bootstrap confidence intervals. |
| Primary | Sensitivity of the multimodal AI algorithms | Through study completion, an average of 6 months. | Sensitivity (recall) will be calculated to assess the ability of the multimodal AI algorithms to correctly identify positive cases relative to the clinician-reported reference standard. Sensitivity will be calculated for each applicable cancer type, with bootstrap confidence intervals. |
| Primary | Specificity of the multimodal AI algorithms | Through study completion, an average of 6 months. | Specificity will be calculated to assess the ability of the multimodal AI algorithms to correctly identify negative cases relative to the clinician-reported reference standard. Specificity will be calculated for each applicable cancer type, with bootstrap confidence intervals. |
| Primary | Area under the receiver operating characteristic curve (AUC-ROC) | Through study completion, an average of 6 months. | AUC-ROC will be calculated to characterize the classification performance of the multimodal AI algorithms relative to the clinician-reported reference standard for each applicable cancer type, with bootstrap confidence intervals. |
| Primary | Intersection over Union (IoU) | Through study completion, an average of 6 months. | Intersection over Union (IoU) will be calculated for applicable object detection and segmentation tasks to assess agreement between AI-generated regions and the corresponding reference standard. |
| Primary | Agreement between AI-generated stratification and the clinical reference standard | Through study completion, an average of 6 months. | Agreement between model-generated lesion stratification and the clinician-reported reference standard will be evaluated using a confusion matrix and quantified using weighted kappa. |
| Primary | Agreement between AI-generated PI-RADS score and the clinical reference standard | Through study completion, an average of 6 months. | Agreement between the model-generated PI-RADS score and the clinician-reported reference standard will be evaluated using a confusion matrix and quantified using weighted kappa. |
| Primary | Agreement between AI-generated Bosniak score and the clinical reference standard | Through study completion, an average of 6 months. | Agreement between the model-generated Bosniak score and the clinician-reported reference standard will be evaluated using a confusion matrix and quantified using weighted kappa. |
| Primary | Agreement between AI-generated RENAL score and the clinical reference standard | Through study completion, an average of 6 months. | Agreement between the model-generated RENAL score and the clinician-reported reference standard will be evaluated using a confusion matrix and quantified using weighted kappa. |
| Primary | Group-stratified performance of the multimodal AI algorithms | Through study completion, an average of 6 months. | Performance metrics of the multimodal AI algorithms will be calculated separately for prespecified participant groups to assess differences in model performance across groups. Group-stratified metrics will be reported with bootstrap confidence intervals. |
| Primary | Group-stratified calibration of the multimodal AI algorithms | Through study completion, an average of 6 months. | Calibration metrics of the multimodal AI algorithms will be calculated separately for prespecified participant groups to assess model calibration across groups. Group-stratified calibration metrics will be reported with bootstrap confidence intervals. |
| Secondary | Acceptability of the COMFORT platform | Through study completion, an average of 6 months. | Clinician acceptability of the COMFORT platform will be assessed using the Technology Acceptance Model (TAM), applicable study questionnaires, and structured interviews. Questionnaire scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. Comparisons between study sites will be performed using non-parametric hypothesis testing. |
| Secondary | Usability of the COMFORT platform | Through study completion, an average of 6 months. | Clinician-reported usability of the COMFORT platform will be assessed using the System Usability Scale (SUS). The SUS provides a total score ranging from 0 to 100, with higher scores indicating greater perceived usability. Scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. Comparisons between study sites will be performed using non-parametric hypothesis testing. |
| Secondary | Perceived trustworthiness of COMFORT AI outputs | Through study completion, an average of 6 months. | Clinicians' perceived trustworthiness of AI-generated outputs will be assessed using the Trustworthiness of AI Output questionnaire and structured interviews. Questionnaire scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. |
| Secondary | Perceived information integration | Through study completion, an average of 6 months. | Clinicians' perceptions of the integration of information provided by the COMFORT platform will be assessed using the Perceived Information Integration questionnaire and structured interviews. Questionnaire scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. |
| Secondary | Perceived effectiveness of the COMFORT platform | Through study completion, an average of 6 months. | Clinicians' perceived effectiveness of the COMFORT platform will be assessed using the Effectiveness of COMFORT Platform questionnaire and structured interviews. Questionnaire scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. |
| Secondary | Care management efficiency | Through study completion, an average of 6 months. | Clinician-reported care management efficiency associated with use of the COMFORT platform will be assessed using the Care Management Efficiency questionnaire and structured interviews. Questionnaire scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. Comparisons between study sites will be performed using non-parametric hypothesis testing. |
| Secondary | AI literacy | Baseline | Clinician AI literacy will be assessed using the study-specified AI Literacy questionnaire and structured interviews. Questionnaire scores will be summarized using the median and interquartile range (IQR) for each study site and across the study. |
Source ClinicalTrials.govtrials-2026-11-12-0.5.0
Sources 3
- ClinicalTrials.gov's posted results, through CTTI's AACTFreely available. Acknowledgement requested
- ClinicalTrials.govNo license stated
- NIH RePORTER's clinical studies and project filesPublic domain
Each source's terms
- ClinicalTrials.gov's posted results, through CTTI's AACTClinicalTrials.gov data via Aggregate Analysis of ClinicalTrials.gov (AACT), CTTI. CTTI makes its materials freely available and requests acknowledgement. https://aact.ctti-clinicaltrials.org/documentation/299
- ClinicalTrials.govnone stated
- NIH RePORTER's clinical studies and project filesPublic domain (NIH RePORTER)
ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.
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