‘Big data’ (as massive data analysis is known) and artificial intelligence (AI) have shown themselves to be two tools increasingly available to researchers and healthcare professionals during this first year of the pandemic. Both weapons that, like everything in these months of ups and downs, have been evolving and adapting to the new reality that the dreaded SARS-CoV-2 has created.
At the beginning of the pandemic, when it had not yet been declared by the World Health Organization (WHO), the first alerts came from Asia. It was the end of January. Then the alarm reached the West and, at the end of February, it was raised in Italy.
However, Bluedot, a Canadian startup, already informed its clients on December 31, 2019 of the spread of a new coronavirus. The algorithm it uses tracks news reports in 65 foreign languages, reports of animal and plant disease outbreaks, official proclamations and even airline data. This way he was able to warn in advance to avoid danger areas such as the Chinese city of Wuhan.
On January 9 of this year, the WHO officially notified the world population of the outbreak of this coronavirus. But the US Centers for Disease Control and Prevention had already given the notice three days earlier.
Epidemiology is the science that studies the spread of a disease and has been using data for its predictions for decades. “Big data provides factors that are proving very important to improve the quality of predictive models,” explains Pedro Antonio de Alarcón, one of those responsible for LUCA, Telefónica’s data unit.
At the same time, AI continues to make giant strides in medicine, although skills and ethics are two battles yet to be fought. “Like all models of this type, the estimates are accompanied by an error, which we try to minimize by improving the diversity and quality of the data and the volume of the samples,” adds De Alarcón.
BlueDot predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei and Tokyo in the days after its initial emergence. To make this diagnosis, a team of 40 employees designed an analytical disease surveillance program, which uses natural language processing and machine learning techniques to track different types of information.
At the same time, artificial intelligence appears more and more frequently in the media, it is another ally in smartphones and also in homes, and in recent times it has been postulated as an attractive solution in business and industry. According to technology provider IDC, spending on AI will grow more than 33% in the services sector alone in the next three years.
In this sense, in the latest report ‘Digital Society in Spain’, prepared by Telefónica, it is highlighted that “the applications of artificial intelligence are already among us; “They range from sophisticated recommendation algorithms for online purchasing of products and services to improvements in the diagnosis and treatment of cancer.” By sectors, health and well-being is where AI is used the most, one in five startups uses it and, in addition, it has been a valuable tool to help beat covid-19.
Reduce ICU stress
Researchers from Queen Mary University of London, together with scientists from IFISC (joint institute of the University of the Balearic Islands and the Higher Council for Scientific Research), have launched an algorithm (NHS) capable of optimally reassigning patients of covid in the ICUs to reduce the stress to which these resources are subjected. According to data from the British public health system, through a mathematical approach and with the help of AI, this algorithm can redistribute up to 1,000 intensive care patients, “who otherwise would probably not receive adequate surveillance,” its creators detail. .
The Basque Health System also used artificial intelligence against covid. The startup Sherpa.ai developed a platform so that health authorities could estimate the number of ICU beds needed over the course of a week. thus avoiding oversaturation of health centers as occurred in other regions. The technology used analyzes patterns and trends in the evolution of the virus, a fundamental aspect so that healthcare workers can react in time. In addition, it is capable of predicting the number of minor hospitalizations, which in terms of logistics would allow, for example, setting up a specific hospital for this type of patient and lightening the rest.
On the other hand, Google’s arm in the health sector, DeepMind, is already trained to detect early cancer through x-rays, specifically lung cancer. A team of researchers has fed a neural network with thousands of images of medical tests, with the aim of it learning to detect the patterns linked to the presence of a certain type of tumor when it is still too small for the human eye to see. appreciate.
In Spain, Francisco Herrera, professor of Computer Science and Artificial Intelligence at the University of Granada, works together with the San Cecilio Clinical Hospital in Granada to apply this model to the diagnosis of covid-19. His project reaches almost a dozen health centers to help locate the virus more quickly and effectively. However, he insists that “the more x-rays, the better the diagnosis.”
Spain falls short of the investments of France and Germany in AI
Six hundred million. It is the figure that the Government is going to allocate to promoting AI in Spain. A plan that is based on six axes of action so that the country “leads the drive for this technology that will transform our economy and society,” says the new National Artificial Intelligence Strategy (ENIA).
In 2018, AI contributed 1.76 billion euros to the global GDP, and it is estimated that its contribution will exceed 14 trillion euros by 2030. Without leaving aside these figures, the first objective of the national plan is to “improve the situation of Spain within artificial intelligence, promote the use of the Spanish language in that field, create employment, incorporate it into the productive fabric” and, likewise, “promote an AI that is inclusive.”
Furthermore, the ENIA is in line with Brussels’ requests to turn this new technological tool into a priority for the economies of the Member States, and thus invest money from European funds in relaunching this digital transformation.
Of the aforementioned 600 million of public investment in Spain, 275 will go to promote the technological development and innovation of artificial intelligence, 133 million to integrate its use in all sectors of the economic fabric, another 100 more to do the same in the Administration Public, 42 million to enhance digital skills talent, another 42 to develop data platforms that support AI and, finally, eight million to create a regulatory ethical framework that reinforces rights and freedoms.
At Moncloa they trust that this strategy will mobilize 3.3 billion in private investment, that is, 5.5 times more. There is also the contribution of the Next Tech fund of a public-private nature, which seeks to promote entrepreneurship in enabling digital technologies.
But the Spanish 600 million fall far short of the euros invested in neighboring countries. Thus, in France they have 1,500 million for the period 2018-2022, and in Germany another 3,000 million to be used between 2019 and 2025.