Taking a selfie and sending it to your doctors is now a cheap and effective method to diagnose your heart disease. The study, published in the European Heart Journal is the first to show that it’s possible to use a deep learning computer algorithm to detect Coronary Artery Disease (CAD) by analysing four photographs of a person’s face.
This novel algorithm has the potential to be used as a screening tool that could identify possible heart disease in people in the general population. “To our knowledge, this is the first work demonstrating that artificial intelligence can be used to analyse faces to detect heart disease,” said study author Zhe Zheng from Peking Union Medical College in China.
“This could be a cheap, simple and effective of identifying patients who need further investigation. However, the algorithm requires further refinement and external validation in other populations and ethnicities”, he added.
For the findings, the research team enrolled 5,796 patients from eight hospitals in China to the study between July 2017 and March 2019. The patients were undergoing imaging procedures to investigate their blood vessels, such as Coronary angiography or Coronary Computed Tomography Angiography (CCTA).
How did they do it?
They were divided randomly into training (5,216 patients, 90 per cent) or validation (580, 10 per cent) groups. Trained research nurses took four facial photos with digital cameras: one frontal, two profiles and one view of the top of the head. They also interviewed the patients to collect data on socioeconomic status, lifestyle and medical history. Radiologists reviewed the patients’ angiograms and assessed the degree of heart disease depending on how many blood vessels were narrowed by 50 per cent or more and their location.
This information was used to create, train and validate the deep learning algorithm. The researchers then tested the algorithm on further 1,013 patients from nine hospitals in China, enrolled between April 2019 and July 2019. The majority of patients in all the groups were of Han Chinese ethnicity.
They found that the algorithm out-performed existing methods of predicting heart disease risk (Diamond-Forrester model and the CAD consortium clinical score). In the validation group of patients, the algorithm correctly detected heart disease in 80 per cent of cases and correctly detected heart disease was not present in 61 per cent of cases.
Cons of the technology
The false positive alarms and restricted ethnicity tested so far are two main cons in the further advancement on this technology. The latter can be resolved in due course of time as the trials are conducted on more diverse regions and people. But the former is the main hurdle before the researchers.
However, the team anticipates to overcome the false positive rates with the further advancement in Artificial Intelligence (AI) algorithms in Image processing and feature extraction.
The scams regarding data misuse of the ethnicity being tested is also a road-block for the development of this technology into the next level, as indicated by Charalambos Antoniades, Professor of Cardiovascular Medicine at the University of Oxford, UK, and Dr Christos Kotanidis, a D.Phil student working under Prof. Antoniades at Oxford in the paper’s editorial.