Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06612606
Status:
COMPLETED
Last Update Posted:
None
First Post:
2024-09-22
Brief Title:
Transfer Learning of a Neural Network for Robotic Surgical Assessment
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Transfer Learning of a Pretrained Preclinical Neural Network for Robotic Surgical Assessment on Limited Clinical Data
Status:
COMPLETED
Status Verified Date:
2024-09
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 goal of this observational study is to explore how pretrained artificial intelligence AI models trained on preclinical data can improve the accuracy of action recognition and skills assessment in robot-assisted surgery RAS in urological patients by the use of transfer learning The main questions it aims to answer are
Can pretrained AI models accurately assess action recognition and skills assessment in clinical surgeries
How do different training approaches of transfer learning affect the performance of the AI models A baseline model developed from scratch using clinical data will be compared to pretrained models that are 1 directly applied to clinical data 2 fine-tuned by training only some layers of the AI model and 3 fully retrained to see if these approaches improve performance
Participants who are robot surgeons will
Undergo RAS procedures on patients with no intervention where video data will be collected for later action recognition and skills assessment
Contribute to model training and evaluation through clinical dataset integration
Can pretrained AI models accurately assess action recognition and skills assessment in clinical surgeries
How do different training approaches of transfer learning affect the performance of the AI models A baseline model developed from scratch using clinical data will be compared to pretrained models that are 1 directly applied to clinical data 2 fine-tuned by training only some layers of the AI model and 3 fully retrained to see if these approaches improve performance
Participants who are robot surgeons will
Undergo RAS procedures on patients with no intervention where video data will be collected for later action recognition and skills assessment
Contribute to model training and evaluation through clinical dataset integration
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