AI Models to Predict Thyroid Cartilage Invasion in Laryng... | NCT06463756 | Trialant

AI Models to Predict Thyroid Cartilage Invasion in Laryng... | NCT06463756 | Trialant

Sponsor/Collaborators Module

Arms/Interventions Module

Interventions

Name	Type	Description	Arm Group Labels	Other Names
AI	Other	Radiomics extracts quantitative information from medical images to generate high-dimensional feature vectors for analysis. It aims to provide insights into disease processes and improve diagnosis. Deep learning utilizes neural networks with multiple layers to learn complex patterns from data. In medical imaging, it enables accurate and efficient analysis for disease detection and diagnosis.

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Area under the curve, AUC	Area under the curve(AUC) is a metric widely used in machine learning and medical research to evaluate the performance of models in binary classification problems. It reflects the ability of a model to identify true positives (True Positives) while avoiding falsely classifying negative examples as positive (False Positives).	Through study completion, an average of 6 months

Secondary Outcomes

Measure	Description	Time Frame
Disease-Free-Survival, DFS	Disease-Free Survival (DFS) refers to the time from the start of randomization (usually the starting point of a clinical trial) to the recurrence of the disease or death of the patient due to disease progression. DFS is an important clinical and statistical indicator used to evaluate the long-term effects of cancer treatment.	The date of surgery and the occurrence of events such as disease progression, the date of the last follow-up, or death from any cause, and the follow-up time was at least 3 years

Contacts/Locations Module

Condition Browse Module

Intervention Browse Module