Uses of Artificial Intelligence in Health Care and How It Helps in Diagnosing Rare Genetic Disorders


Artificial Intelligence (AI) has greatly impacted nearly every industry. It has brought innovation in machine learning and transformed various sectors such as education, finance, and healthcare.

Artificial Intelligence aims to create machines as intelligent as humans. In recent years, there has been a number of activities carried out with the help of Artificial Intelligence such as speech recognition, distance learning and problem-solving.

In medical applications, the usage of this technology has become substantial. The medical industry, recently, was buzzed with the news that a group of algorithms that analyze images, can diagnose the rare genetic disorders in human with the help of the patient’s facial images. This technology, called DeepGestalt, is developed by a digital health startup FDNA, based in Boston.

The Innovation Makes Sense for the Doctors:

This technology can diagnose rare genetic disorders in patients with the help of their facial photos- a diagnosis which is difficult for human doctors. This means that in the near future, facial recognition can become a vital part of a medical checkup, helping doctors and clinicians in speed up the diagnosis procedure.

According to the journal, Nature Medicine, “syndromes genetic conditions affect 8% of the population”. It further states that there are various syndromes, which have recognizable facial features that prove to be helpful in clinical geneticists.

DeepGestalt Outperforms Doctors:

According to recent research, the facial analysis technologies equals up to the expertise of the doctors in the identification of syndrome. But, it is important to remember that these technologies could identify only certain genetic diseases, which means their role in the clinical setting is limited. Because it further requires hundreds of another diagnosis to be considered.

With the DeepGestalt facial feature analysis framework, it uses computer vision as well as deep-learning algorithms, which evaluates similarities to hundreds of this syndrome. In initial experiments, DeepGestalt outperformed doctors; in the final experiment in a real clinical setting, this framework achieved 91% of accuracy in diagnosing the correct syndrome by analyzing 502 different facial images. This technology could identify syndromes such as Angelman syndrome and Noonan syndrome. Given the phenotypic evaluations, DeepGestalt adds considerable value in genetic testing, clinical genetics, precision medicine, and research.

The chief technology officer of FDNA said that this approach is though not perfect, but definitely much better than a human trial. With the help of the application of deep learning algorithm to facial characteristics of the pictures, this technology diagnoses the possible syndromes.


FDNA has developed an app called Face2Gene to diagnose the syndromes. This application identified rare genetic disorders by analyzing more than 17,000 images or people who were already diagnosed with genetic syndromes. With the help of this data, the app identified distinctive facial features relevant to the particular disorders.

Other Uses of AI in the Medical Industry:

Apart from the diagnosis of rare genetic disorders, there are other highly effective and transformative uses of artificial intelligence in the medical industry. According to research, by 2020, healthcare organizations and technology vendors will spend $54 million on average on the projects associated with AI. Other solutions that this technology is going to implement in this industry are:

  • Management of Medical Records and Data:

Given the process of compiling and analyzing information such as medical history and records, data management is a very popular and useful application of artificial intelligence in the medical industry. Robots, collect store and trace patient’s data swiftly and efficiently.

  • Completing Common Tasks:

AI robots can for sure help in carrying out mundane tasks such as analysis of tests, X-Rays, CT scans o data entry accurately and faster. In the disciplines of cardiology and radiology analysis of data can become time-consuming. In the future, doctors can work on complicated cases that require human intelligence and supervision.

  • Digital Consultation:

Interestingly, applications like Babylon use artificial intelligence to assist the doctors in medical consultation on the basis of personal medical history and medical knowledge, the app then offers a recommended action.

  • Digital Nurses:

The digital nurse helps people in monitoring a patient’s condition and follow up treatment. It provides basic health information to the parents and advises whether the current condition needs a doctor or not.

  • Precision Medicine:

AI can help point out cancer and vascular diseases quite earlier as well as predict possible health problems in people based on their genetics.

Artificial Intelligence is famous for its highly useful applications and its brilliant ability in processing and managing data at a large scale. Given the vast potential and usage of AI in the medical industry, there will be more time saving and accurate medical procedure in the near future with low cost and increased efficiency.

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