Medicine and Artificial Intelligence

The medical sector is showing great interest in Artificial Intelligence and especially in Machine Learning techniques capable of providing better tools to healthcare professionals and more personalization of patient care.

Over the years, more and more disciplines are showing great interest in artificial intelligence: one of these is the medical sector provides better tools available to doctors. Not only that: the recent deep learning techniques could allow shortly to have fully automated phases of therapies, allowing doctors and operators in the sector to devote themselves more to the study of new solutions.

According to research by Frost & Sullivan, the market for AI in healthcare will reach 6 billion dollars in 2022, with an annual growth rate of 68%, generating savings of over 150 billion dollars.

Applications of Artificial Intelligence:

In the year of the pandemic, a driving factor was the adoption of artificial intelligence technologies by pharmaceutical and biotech companies around the world to accelerate the development processes of vaccines or drugs against COVID-19. Partnerships between pharmaceutical companies and technology companies are multiplying, to analyze large data sets and discover new correlations to develop drugs in a short time and with lower costs. Microsoft, for example, has created the “Covid Moonshot” project, which sees the commitment of pharmaceutical companies, universities, and technology companies in the search for solutions to the pandemic.


Through the use and interpretation of data, the first signs of some diseases can be detected to help doctors make more accurate diagnoses, reduce errors, and develop methods for individualized medical treatment.

Among the fields that are attracting many investors, there is rehabilitation, with machines capable of learning from the exercises of the physiotherapist and then replicating them on the patient, and medical imaging. Artificial intelligence can support the decision-making process of radiologists, improving diagnostic activity.


In a nationwide healthcare system, with thousands of doctors working with as many patients, there may be variations in the way certain symptoms are treated. An ML algorithm can detect these natural variations to help doctors identify one preferred treatment over another. One application could be to compare what the doctor would prescribe to a patient with a treatment suggested by an algorithmic model.

Artificial intelligence can be a powerful tool in the service of modern medicine. And in part it already is. The applications multiply in all areas, from diagnostics to surgery, from drug development to rehabilitation.

A task force, enhanced with artificial intelligence, quickly prioritized hospital activity for the benefit of all patients. Since implementing the program, the facility has seen a 60% improvement in inpatient admission capacity and a 21% increase in patient discharges before noon, resulting in a faster and more positive patient experience.


Despite all this, largely due to the acceleration imposed by the emergency resulting from the Covid-19 pandemic, there are some obstacles to the easy spread of AI-based technologies, among which we can mention the reluctance of some doctors to adopt technologies (almost always due to inadequate training) and the lack of a specifically qualified workforce, for which there is a real skill shortage from a technical point of view that must be bridged with suitable and specific training programs that involve an audience of operators more and more wide and varied.

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