Trial · NCT07888322

Assessment of Intelligent Algorithms for Detection, Diagnosis and Risk Stratification of Tumors of the Kidney and Prostate

NCT07888322, Not yet recruiting, Aristotle University Of Thessaloniki

3 sourcestrials-2026-11-12-0.5.0

Cite this record

ConductScience Library. Assessment of Intelligent Algorithms for Detection, Diagnosis and Risk Stratification of Tumors of the Kidney and Prostate. Trials, record NCT07888322. Release trials-2026-11-12-0.5.0, 12 Nov 2026. https://conductscience.org/library/trials/NCT07888322

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Trial

As registered on ClinicalTrials.gov, in the graph's capture of the registry.

Title: Assessment of Intelligent Algorithms for Detection, Diagnosis and Risk Stratification of Tumors of the Kidney and Prostate
NCT number: NCT07888322
Status: Not yet recruiting
Enrollment: 50 participants, estimated
Lead sponsor: Aristotle University Of Thessaloniki
Conditions: Kidney Cancers, Prostate Cancer
Interventions: Medical Reading, AI assisted Medical reading
First posted: 2026-10-22
Last updated: 2026-11-02

Source ClinicalTrials.gov

Registered outcomes23

Each outcome the trial registered, primary first, in ClinicalTrials.gov's words.

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.

1 to 10 of 23Source ClinicalTrials.gov

See all 23 registered outcomes

Outcomes0

Each outcome the trial posted results for, in ClinicalTrials.gov's words.

None in this release.

Results by group0

Each measurement the trial posted, group by group, in the words and numbers it posted.

None in this release.

Participant flow0

How many started, completed or left each group, period by period.

None in this release.

Adverse events0

Each adverse event the trial posted, group by group: the participants affected out of those at risk.

None in this release.

Adverse event totals0

The totals the trial posted for each group.

None in this release.

Papers0

The papers the trial lists on ClinicalTrials.gov.

None in this release.

Grants0

The grants NIH RePORTER links to the trial, newest funded first: NIH's, and some of AHRQ's, CDC's, FDA's and VA's. Each shows its title, principal investigators, organization and funder in its newest year.

None in this release.

Trial comparisons0

Comparisons of the trial's two groups, calculated by ConductScience from the counts it posted.

None in this release.

Tests0

The ConductCognition tests this trial's registered outcomes name, as ScienceGraph matched them in trial-tests-2026-11-12-0.2.1.

None in this release.

Data dates

The day each source was copied for this release.

ClinicalTrials.gov: 2026-11-12; ClinicalTrials.gov
Results, from AACT: 2026-03-23; AACT
NIH grant links: 2026-11-13; NIH RePORTER

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.

For software

Read this trial from software.

The record and each of its lists are JSON, twenty rows a page. No key.

GET https://conductscience.org/api/trials/v1/NCT07888322

GET https://conductscience.org/api/trials/v1/NCT07888322/registered?page=2

API reference For AI assistants