Outcome
Type |
Measure |
Description |
Time frame |
Safety issue |
Primary |
To develop and train a convolutional neural network to detect and characterise disease severity of inflammatory bowel disease during endoscopy |
To develop and train a convolutional neural network to detect and characterise disease severity of inflammatory bowel disease during endoscopy |
5 years |
|
Secondary |
a) To explore whether Artificial Intelligence can predict response to IBD therapies |
To explore whether Artificial Intelligence can predict response to IBD therapies |
5 years |
|
Secondary |
b) To develop an endoscopic image repository to advance training and standardisation in endoscopic detection and characterisation of IBD. |
b) To develop an endoscopic image repository to advance training and standardisation |
5 years |
|
Secondary |
c) To develop and assess methodologies for training and quality assurance of IBD diagnostic endoscopy |
To develop and assess methodologies for training and quality assurance of IBD |
5 years |
|
Secondary |
d) To evaluate comparisons in endoscopic image interpretation between endoscopist's |
To evaluate comparisons in endoscopic image interpretation between endoscopist's |
5 years |
|
Secondary |
e) To develop deep learning algorithms and computer vision techniques to allow for automated measurement of quality metrics in endoscopy for IBD |
To develop deep learning algorithms and computer vision techniques to allow for automated measurement of quality metrics in endoscopy for IBD |
5 years |
|
Secondary |
f) To create a future robust research platform to ensure the above objectives are continuously developed as novel imaging techniques emerge over time. |
To create a future robust research platform to ensure the above objectives are continuously developed as novel imaging techniques emerge over time. |
5 years |
|