Doctors can use selfies to detect cardiovascular disease

Who thought sending a self-portrait to a doctor could help detect heart disease? According to new research, send Selfie An inexpensive way to diagnose cardiovascular disease.

Published in the European Heart Journal, this study has shown how deep learning-based computer algorithms analyze four pictures of a person from different angles.

This new method requires further research and testing on large numbers of people from different ethnic backgrounds to prove it is accurate and true, but this new technology for selfie analysis I have great expectations.

(Photo: Getty Images)
HAMBURG, GERMANY-MAY 25: People take a selfie while enjoying the scenery at the resumption of the Elbphilharmonie after being closed during the coronavirus crisis in Hamburg, Germany on May 25, 2020. (Photo: Stuart Franklin / Getty Images)

Use of SELPHY in the detection of coronary heart disease (CHD)

Professor Zhe Zheng, who oversaw the research and headed the Deputy Director of the National Cardiovascular Center, head of the Chinese Academy of Medical Sciences and the President of Beijing Medical University, Fuhe Hospital, said that their research was based on artificial intelligence (AI) coronary arteries. Used to detect faces in the detection of heart disease (CHD).

He also noted that it is a step towards developing a deep learning-based tool that allows outpatients to assess their risk of heart disease, take selfies, and screen themselves.

In addition, Professor Chung said their main goal is to create a self-assessment application for high-risk communities to assess the risk of heart disease prior to visiting the clinic. .. According to them, it is cheaper, easier, and an effective way to detect patients in need of further evaluation.

However, algorithms that examine these selfies need to be further refined and tested on other groups and ethnic groups.

Studies show that certain facial features are associated with heart disease. These are found on the ear wrinkles, wrinkles, thinning hair, or gray hair. xanthelasmata,and Arch cornea.. However, they are difficult to accurately predict and quantify the risk of heart disease.

From July 2017 to March 2019, 5796 patients from 8 different hospitals in China were studied with Professor Zheng by Professor Xiang-Yang Ji of Brain Cognition Institute of Department of Automated Chemistry of Tsinghua University.

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Researchers have coronary angiography or Coronary computed tomography angiography (CCTA) Examine participants’ blood vessels. The team then divided the patients into training (90%) and validation (10%) groups.

The patient was taken at four different angles. One is a front view, two are profiles, and the other is a photograph seen from the top of the head. The nurse interviewed the participants and used the information they collected to build a deep learning algorithm.

Next, the algorithm was tested on 1,013 patients of Han Chinese. This algorithm was found to be better at predicting heart disease risk than existing methods such as CAD Consortium clinical scores and the Diamond-Forrester model.

How effective are the new ways to predict the risk of heart disease?

According to Professor Ji, the algorithm has moderate performance and can be used to quickly predict the risk of heart disease based only on a person’s photo. The nose, forehead, and cheeks contributed more to the algorithm than the rest of the face.

However, its specificity still needs improvement as it can indicate false positives. Taking selfies as a way to screen for heart disease risk provides an easier and more effective way to screen the general population to avoid unnecessary clinical evaluation.

Self-portrait analysis can also be useful in areas where funding is scarce and may have weak cardiovascular screening programs. As easy as taking a selfie, people can use CCTA to take a primary diagnostic test.

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