Over the past few years, we have experienced an exponential increase in data creation. From when our smartphone tells us how many steps we take, to count the times we get on public transport, to how many megabytes we spend on our mobile data rate.
Just as this data is generated from our daily lives, it the same happens in the clinical environment: the number of times we visit the emergency room, the occasions we suffer hospital admissions, the number of drugs prescribed or the X-rays taken throughout our lives, among others.
The immense amount of data is far beyond human analytical capacity. It requires technology that is capable of storing, processing and protecting this valuable data. Therefore, it is not only the help of computers necessary but also artificial intelligence and algorithms. And thanks precisely to these and other tools (deep learning, machine learning) in recent years are making many discoveries, in addition to predicting future scenarios in terms of epidemiology, as is the case of urogenital cancer.
Another example of these new tools, this time deep learning: Case in which the machine learns to recognize a series of patterns, in this example, has been the analysis of ophthalmological fundus. Today we know the relationship of the ocular fundus and its relationship with heart disease. What we were not able to predict and with such a high level of accuracy was the risk, as well as other parameters. The machine analyzed more than 200,000 patients and has been able to identify not only risk patterns but also the sex of the participating population, through the thickness of the eye's veins alone—something that human capacity has not achieved, impossible to date.
AI and pharmacogenetics:
Also, significant advances are forthcoming in the field of pharmacogenetics. Can you imagine that we will not have to test new drugs in human and non-human animal populations? Various teams are already carrying out this type of research. Through the use of artificial intelligence and massive data, the possible impact that multiple drugs can have on the population is already in study.
AI here to stay:
Artificial intelligence arrived a few decades ago to stay, and not in vain. We will see in the future how all this massive amount of mass data will impact the world's population. For the moment, the foundations of what should be a universal ethical framework are already ongoing. And that ethical framework must address universal principles such as transparency, fairness, non-maleficence, accountability and privacy.