Ignite Creation Date:
2024-10-26 @ 3:36 PM
Last Modification Date:
2024-10-26 @ 3:36 PM
Study NCT ID:
NCT06534814
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-07-25
Brief Title:
Development and Application of an Artificial Intelligence-driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Hebei Medical University
Status:
RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The clinical trial titled Development and Application of an Artificial Intelligence-Driven Accurate Identification Model for Gastric Cancer Lymph Node Metastasis aims to enhance the detection and treatment of gastric cancer through the utilization of cutting-edge artificial intelligence AI technology This study will develop an AI-driven model designed to accurately identify lymph node metastasis in patients with gastric cancer which is crucial for staging the disease and planning effective treatment strategies
The trial will involve a multidisciplinary team of oncologists radiologists data scientists and AI experts who will collaborate to create a robust and precise identification system Participants will undergo standard diagnostic procedures and the AI model will analyze imaging and pathological data to predict lymph node involvement
By comparing the AI models predictions with traditional diagnostic methods the study seeks to validate the models accuracy and efficiency This approach is expected to improve early detection rates reduce diagnostic errors and ultimately lead to better clinical outcomes for patients with gastric cancer The successful implementation of this AI-driven model could revolutionize the current standards of care and serve as a blueprint for integrating AI technologies in other cancer diagnoses and treatments
The trial will involve a multidisciplinary team of oncologists radiologists data scientists and AI experts who will collaborate to create a robust and precise identification system Participants will undergo standard diagnostic procedures and the AI model will analyze imaging and pathological data to predict lymph node involvement
By comparing the AI models predictions with traditional diagnostic methods the study seeks to validate the models accuracy and efficiency This approach is expected to improve early detection rates reduce diagnostic errors and ultimately lead to better clinical outcomes for patients with gastric cancer The successful implementation of this AI-driven model could revolutionize the current standards of care and serve as a blueprint for integrating AI technologies in other cancer diagnoses and treatments
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None