King's College London

One in two people will be diagnosed with cancer at some point in their lifetime. If cancer is identified early, the chances of survival are more than 80 per cent at 10 years but, when diagnosed late, survival falls to less than 30 per cent at 5 years.

Yet diagnosing cancer is extremely challenging. Unlike other diseases, there is no single identifiable symptom or test that can alert doctors to a potential cancer diagnosis.

C the Signs is a clinical platform that uses artificial intelligence mapped with the latest evidence and research to identify patients at risk of cancer at the earliest and most curable stage of the disease. Covering the entire spectrum of cancers, C the Signs can identify patients at risk of cancer in under 30 seconds, accurately detecting the type of cancer(s) the patient is at risk of and recommending the most appropriate next step.

C the Signs uses a conditional logic model with combinations of risk factors, symptoms, clinical signs and investigation results to determine if a patient is at risk of cancer and what the next step should be (eg a blood test, scan or referral to a specialist). We are currently building the most advanced machine learning model to detect cancer even earlier.

Project Team

Bhavagaya Bakshi (King's Medicine alumna) & Miles Payling
C the Signs