Artificial intelligence between analysis and prevention: this is how it will heal us

Predictive medicine and evaluation clinic in the cases of stroke ischemic: theASL Lecce relies onartificial intelligence to refine assistance and improve care even in pathologies time employees. The two projects already activated by the healthcare company actually focus on knowledge of chronic diseases in the population and aim to develop the appropriateness of therapies, so as to identify the best treatments and predict patients’ response.

The “e-Stroke” project

In detail, one of the activities developed by the diagnostic and interventional neuroradiology unit of the “Vito Fazzi” hospital, led by Adriana Paladini, is the “e-Stroke” project aimed at supporting doctors in the initial evaluation of stroke on CT scan without contrast , CT angiography, perfusion and MRI scans.
The image and algorithm system provides a rapid and coherent calculation of scientific and clinically relevant scores, including the ischemic core (tissue already in necrosis), which allows doctors to identify the type of intervention, to be cross-referenced with health assessments, for the decision on the most appropriate treatment to perform on the patient. “In time-dependent pathologies – says head doctor Adriana Paladini – timely treatment is fundamental. The technological software therefore allows us to identify the level of occlusion suffered by the patient, as well as being able to evaluate the recoverable ischemic tissue compared to that in necrosis already affected by a stroke. The patient’s computer study is added to the professional’s clinical assessments, in order to make the appropriate choice for the case. Furthermore, the data put online connects the peripheral hospitals with the central structure. Artificial intelligence, introduced in the department for the first time 6 years ago and applied for thousands of treatments on patients from the provinces of Lecce and Brindisi, is therefore an excellent support for the medical activity – Paladini specifies – which must however remain the starting point in every treatment decision”.

Predictive medicine

In the field of predictive medicine, however, the second project launched by the Lecce Local Health Authority led by General Manager Stefano Rossi, aims at knowledge of the epidemiological profile of the assisted population and of the indicators related to health needs and the outcomes of the care interventions carried out, which are essential for a good health planning.
“This model, which uses information relating to the person’s clinical, healthcare and social needs – is highlighted in the project sheet – has the aim of identifying appropriate, sustainable and personalized interventions”. Through the insertion of a set of values ​​into the network (for six population groups: healthy people, occasional patients, mono-morbid chronic patients, multi-morbid chronic patients, non-self-sufficient subjects and people in a terminal state), a system will be created of territorial governance which allows the identification of intervention priorities, with particular reference to the continuity of care for individuals in chronic/frail conditions and disabilities which involve the risk of non-self-sufficiency, also through the integration between the social and healthcare systems .

Artificial intelligence therefore makes it possible, in particular for the treatment of chronic diseases, to develop population management systems (PHM) capable of moving from retrospective to prospective analysis, aimed at predicting the risk of unfavorable progression towards worse stages of illness. In essence, the local health authority and doctors will be able to intercept health needs in advance with a predictive epidemiological model, which allows the preparation, through population stratification, of useful tools to improve and adapt to needs, thus directing interventions by the local medicine and hospital specialists, as well as the entire network of social and health services.

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