Artificial Data and Intelligence, the keys to advancing the diagnosis of Autism
A scientific study published in the magazine Nature concludes that the technologies of big data and artificial intelligence (AI) will provide an impulse for the diagnosis of cases with autism spectrum disorders (ASD), since they help to break down in detail the case variables that form a very heterogeneous population and with many differences between them.
According to this study, the big data allows large samples with multiple parameters to be classified instead of smaller, homogeneous groups, as has been the case up to now. In this way, psychiatrists and researchers will be able to take into account all genetic, neuronal, cognitive and behavioural factors to establish much more precise diagnoses of potential ASD cases.
The exact number of cases is not known
The detection and diagnosis of ASD up to now presented great difficulties. In fact, the Confederation of Autism of Spain admits that it does not know with certainty the number of cases that exist in our country, although in recent years it has found that the cases detected and diagnosed has increased, thanks in part to A more precise diagnosis of diagnostic procedures and instruments is essential. For this reason, technologies such as big data, data virtualisation and artificial intelligence, which allow all the variables involved to be categorized and taken into account in the cases, can be of enormous help, not only for diagnosis, but also for improving the quality of life of people with this disorder.
Ali Rebaie, a data anthropologist and expert in artificial intelligence, big data and other technologies such as data virtualisation, points out some ways in which these technologies can help people with autism. Such as early and intelligent diagnosis, which can have a huge positive impact on children’s development. This is what the Nature study says, which alludes to the fact that these technologies that handle a large amount of data from multiple variables can help to speed up and refine diagnoses.
Rebaie also speaks of prediction with neuroscience and AI, since the data provided by brain imaging provided by magnetic resonance imaging could be introduced into machine-learning algorithms in order to be able to analyse future images and predict other cases; or real-time behaviour analysis, which would allow greater control of patient activities. With the help of a gadget that monitors the individual’s heart rate, anxiety levels, exercise, or sleep patterns, virtualisation of data would allow access to this information for real-time research and analysis. By doing this, professionals can make better decisions based on the analysis of data behaviour.
Data-based robots, or machines that are able to learn, interpret, and recognize the behavioral signs of a child with autism, helping to predict emotional states and methods to better connect with them; and intelligent voice assistants with artificial intelligence, which may also soon be included in devices that can have natural conversations with patients to improve, in particular, their speech skills, are other options highlighted by the expert anthropologist.
All these uses show how the above technological innovations could play a very important role in the future of health. An example of this, says the Galician company Denodo, is the virtualization of data, which allows data access and processing in a unified, simplified and integrated way in real time. And with the guarantee of the security and privacy of personal data, a crucial aspect considering the confidentiality of this information.
