# The Construction and Effect Verification of a Deep Learning-based Automated Semantic Segmentation Model for Medical Imaging

> **NCT06864702** · NA · ENROLLING_BY_INVITATION · sponsor: **Zhujiang Hospital** · enrollment: 220 (estimated)

## Conditions studied

- Artificial Intelligence (AI)
- Deep Learning
- Laparoscopic Surgery

## Interventions

- **BEHAVIORAL:** Whether the patient received diagnosis and treatment at Zhujiang Hospital of Southern Medical University and retained medical images such as abdominal

## Key facts

- **NCT ID:** NCT06864702
- **Lead sponsor:** Zhujiang Hospital
- **Sponsor class:** OTHER
- **Phase:** NA
- **Study type:** INTERVENTIONAL
- **Status:** ENROLLING_BY_INVITATION
- **Start date:** 2023-12-20
- **Primary completion:** 2025-03-20
- **Final completion:** 2025-05-15
- **Target enrollment:** 220 (ESTIMATED)
- **Last updated:** 2025-03-07


## Primary source

ClinicalTrials.gov registry: https://clinicaltrials.gov/study/NCT06864702

## Citation

> US National Library of Medicine, ClinicalTrials.gov registration NCT06864702, "The Construction and Effect Verification of a Deep Learning-based Automated Semantic Segmentation Model for Medical Imaging". Retrieved via AI Analytics 2026-06-25 from https://api.ai-analytics.org/clinical/NCT06864702. Licensed CC0.

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