ARTIFICIAL INTELLIGENCE CLINICAL EVALUATION (AiCE)
A Clinical Evaluation Report (CER) documents the conclusions of a clinical evaluation of your medical device. It consists of the data collected and analyzed from either from a clinical investigation of your medical device, or the results of other studies on substantially equivalent devices. The CER therefore evaluates whether your device achieves its intended purpose without exposing users and patients to further risk.
Clinical Evaluation Reports are required for all medical devices in Europe. You must submit your CER to your Notified Body as an attachment to your European CE Technical File. The Technical File is an essential step to obtaining CE Marking for your device, which is required to sell or distribute medical devices in Europe.
About AiCE- (Artificial Intelligence Clinical Evaluation)
A clinical evaluation takes place in three steps:
AiCE is an LTTS’ integrated AI tool perform systematic review and reporting related to clinical literature, along with any other additional databases that may be added to the report for their inclusion in CER
AiCE tool, with its cognitive capabilities, provides a near-perfect solution for literature search, improving efficiency, cost-effectiveness, speed, and accuracy of CER research.
The tool reduces bias, shrinks the need for multiple searches through algorithm reuse and customization, allows for auto-translation of sources in other languages, and can speed up the process of literature selection and extraction by orders of magnitude, significantly decreasing the time taken for manually searching and filtering appropriate content.
AiCE screens literature and highlights important 2-3 sentences in the different methods of screening
To have a transparent and objective approach for this literature review, to the tool adopts a five-stage approach:
Ver. 1.0
1
User Management/Role-based access management
2
Roles – Manager, Researcher, Quality Analyst
3
Dashboard and Reports
4
Project Creation and Workflow Management
5
AI-assisted literature Pre-Screening
Ver. 1.0
Ver. 1.1
Ver. 1.1
1
Provision to configure device-specific procedures in the project tab
2
Enable PICO entity recognition
3
Integrate with one more research database
4
Configure and select pre-set criteria for article inclusion and exclusion
5
Second pass screening on full-text articles
6
PRISMA chart
Benefits
