Our objective is to develop a complete patient pathway that enables high-quality diagnostics, which considers patient preferences and ethical and economic considerations.
The first stage of the AICE patient pathway utilises powerful algorithms driven by AI. These algorithms are designed to analyse various factors and indicators, such as medical history, risk factors, and prior test results, to identify patients who would benefit most from CCE. This stage aims to determine the most appropriate procedure for each patient, with two possible outcomes: traditional OC or CCE.
If CCE is recommended, patients are provided with guidance for bowel preparation, vital for optimal imaging quality. They can then ingest a specialised capsule with an embedded camera from the comfort of their home. The capsule travels through the colon, capturing up to 50,000 images for a comprehensive visual assessment. Subsequently, these images are automatically uploaded to a secure system to enable thorough evaluation.
AI algorithms direct the analysis stage, examining extensive visual data from the investigation phase. With exceptional processing and pattern recognition capabilities, AI detects subtle changes that may be missed by the human eye. The resulting diagnostic AI report delivers a comprehensive assessment of the colon’s condition. By standardising assessments and avoiding human reader variability, this stage delivers prompt, reliable and accurate analysis.
Healthcare professionals use their expertise, clinical judgment, and the objective information provided by the AI report from the analysis stage to establish a conclusive diagnosis. This pivotal stage fosters collaborative decision-making between healthcare professionals and patients, enabling open discussions. These interactions empower patients to actively engage in their healthcare journey, leading to personalised and optimal courses of action.