As a result of the COVID-19 pandemic, precision medicine has been reaffirmed as a key tool thanks to the advances made in Artificial Intelligence and Big Data. Among some of the most important advances achieved is the ability to advance the prognosis of the disease based on the profile of each patient, something that can be deduced from international research Big COVIData. Through the use of Savana platform technology, it has been possible to launch quality clinical responses and predictions in record time to improve prevention, research and medical management.
This was stated during the Coronavirus webinar a year later: The evolution of clinical research with Artificial Intelligence. Precisely in him, Ignacio H. Medrano, medical director and founder of Savana, wanted to highlight the benefits of machine learning in the health sector. According to Medrano, this is about giving the computer “the problems solved, in such a way that they only infer the rules. This allows them to anticipate new problems even if it is the first time they see it.”
In this sense, the great evolution experienced since 2013-2014 has favored a greater handling of data that has resulted in benefits for this type of technology, which is already noticeable in predictive models such as the current ones. Thus, Medrano referred to the help that machine learning already entails, which has also borne fruit in the diagnosis. In fact, at this time COVID, for example, has made it possible to reposition drugs more quickly in ICUs.
The profits obtained have thus sought its research and development in Spain, which has eventually led to the aforementioned Big COVIData. In this way, the work delves into four investigations, carried out in Castilla-La Mancha, in which techniques of this depth have been used.
Great COVIData and EPOC
The macro-study includes analysis on the impact of COVID-19 in patients with COPD, asthmatics, gender differences in diagnosis and the profile of the patient to be admitted to the ICU. One of the conclusions of the new research is that COVID-19 affects more people over 40 with respiratory diseases, although it does not impact everyone equally. In the case of Chronic Obstructive Pulmonary Disease (COPD) the risk of contracting coronavirus doubles compared to the general population and when this happens, the chances of dying triple.
According to the results published in the “Journal of Clinical Medicine” of the specific analysis on “Characteristics and prognosis of COVID-19 in patients with COPD”, led by the University Hospital of Guadalajara and the Hospital de la Princesa de Madrid, along with Savana technology, patients hospitalized with coronavirus in addition to COPD have a mortality rate of 9.3 percent, compared to 3.4 percent among those over forty who suffer from only VOCID- 19.
The patient with COPD most likely to contract COVID-19 is a man in 4 out of 5 cases, 75 years of age and added pathologies.
In addition, he points out that the patient with COPD most likely to become infected is a man in 4 out of 5 cases, aged 75 years of age and added pathologies (diabetes, arrhythmias, heart failure, etc.). In addition, pneumonia is the most common diagnosis among those hospitalized with COPD and coronavirus. With asthmatics, however, although the frequency of coronavirus infection is higher than among those who are not, the impact of COVID-19 is considered lower.
The future of AI: growth and challenges
In terms of health, the explosion of the data is “very obvious”, according to Yolanda González, lead international team of Hospitals and Research of Savannah. In fact, as he pointed out during the meeting, from 2013 to 2020, we have been generating 157 percent more information in the health sector that we have been climbing the cloud.
The source of all this information is very varied, as according to the expert it goes “from the smartwatch that is collecting and monitoring our activity”, through the questions we ask Google about symptoms, to the records electronic clinics. “All this data is being uploaded to the cloud, and if analyzed correctly, it will lead to a much more efficient medicine, known as precision medicine,” González said.
However, for all this to be possible and for such models to thrive, three barriers need to be overcome. These are the privacy of health data; the storage of a large amount of information; and the accessibility of this information from the work centers and from the hospitals themselves.
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