The applications of Artificial Intelligence in the field of health are in full development all over the world. This sector is showing a dizzying increase (*) in all categories of use of AI in the medical field.

Just to give some examples of solutions already in existence:

• innovative medical devices (for example wearable devices);
• Imaging devices (improvement of image quality for early detection of diseases);
• management of chronic diseases (for example, Machine Learning to monitor the protocols used on patients and automate the administration of drugs via the App);
• data collection in the field of health (for example the Health Electronic Records in the USA, which communicate all the health data relating to all patients in order to develop predictions on the therapies and the quantity of doctors needed, or the Artificial Intelligence platform in Medical Epidemiology).

With regard to the last point, it is obvious that in the medical field Data analytics allows to process an infinitely greater amount of information than that possible for any pool of doctors. It is equally obvious that the spread of AI systems poses important dilemmas regarding respect for privacy and the relevant issue of bias (if an algorithm is trained to study a certain type of disease only on clinical cases of a sex, or of a certain age group, will inevitably be subject to a distortion in the result).

"Data analysis can support healthcare decision making, but the decision must be left to man," Professor Wullianallur Raghupathi of Fordham University in New York recently said in an interview.

Always keeping in mind this fundamental directive, Big Data Analytics techniques and AI applications in the medical field can guarantee exceptional developments in diagnoses, in the administration of treatments, in the precision pharmacy, in personalized medicine, in predictive medicine, in the development of Apps that can detect health conditions in real time, or even more simply that facilitate and guide the patient and his family members on a hospital journey.

Even in Italy Digital Health is becoming a priority for Italian healthcare facilities, but although many virtuous examples of new applications already in use are born every day, in general the companies in our healthcare system seem to travel with the brake engaged, primarily because the Digital Health needs continuous investments and trained / dedicated staff that are almost never available, but also for an attitude that is still too "lazy" towards everything that is innovative.

The field of health training it is a perfect example of this low propensity for innovation. While health claims have changed who come from the community, the figure of the patient has changed, and is increasingly “expert” and technological, the way of training and updating those who carry out and will carry out medical practice in the coming years has not evolved as well.

Even today, classroom training is the most widespread type of education in healthcare, despite a slight increase in laboratory training, located training and distance learning events. And above all the classroom is still identified with the frontal lesson.

While today the possibilities of facilitating learning with a high added value for medical professional practice and for the quality of care are extremely broad, and the design of educational paths - whether in the classroom or remotely - must take these fundamentals into account principles:

- medical learning is facilitated if the teaching takes place in a relevant and realistic context;

- learning is a collaborative process, in which learners bring their needs and experiences;

- it is necessary to value the exercise of critical thinking, flexibility, problem solving orientation, team work;

- in the health field, the experiential didactic value of a clinical laboratory (even interdisciplinary), of an internship, of a bedside training, of a situated training, are infinitely superior to that of any theoretical lesson.

Precisely for all these reasons we protagonists of training must be ready for the challenge and we cannot help supporting the evolution of Digital Health with the introduction of new methodological and didactic tools.


For health education we have many e-learning solutions that offer the possibility of reconstructing training situations immersive, simulations, illustrations of real cases:

Case Study and Visual Storytelling.

Construction of a story, in the first real case, in the second fictitious case but set in a realistic health context that allows you to contextualize the topics covered and to feel immersed in reality. The story represented can also be interactive, so that the learner can influence the outcome of the events.

Simulations, Serious Games, Virtual Gyms.

Educational games or simulations that train decision-making skills in situations involving multiple practical and emotional variables. Interactive simulation is a didactic typology that has the fundamental purpose of developing skills and competences to be applied in the real world through exercise in a simulated and protected environment, and therefore adapts very effectively to a context such as healthcare in which it is necessary to experiment. ex ante and train decision-making skills and / or use of specific tools.


The production of content on video it has now become an integrated tool in many online courses, but it can also become the main tool for the delivery of educational content. The Video involves the learner, activates their attention and interest, and offers the possibility of simplifying the description of cases, situations and tools. It is a perfect tool to illustrate the characteristics and potential of a new medical device, or to illustrate a procedure with a real situation.

(*) KPMG reports a constant growth of 5% per annum in the sale of medical devices with AI solutions, and according to Accenture the sector will produce 6,6 billion dollars in 2021 compared to 600 million recorded in 2014.