Publications by authors named "Marco DI Francesco"

Article Synopsis
  • AI has evolved since its introduction in 1956 and is now significantly impacting healthcare, especially in patient care and information management.
  • Key AI functions like Machine Learning and Deep Learning, along with Biomimetic Intelligence, are being utilized to analyze medical data and create algorithms for better diagnosis and treatments.
  • The rising incidence of chronic limb-threatening ischemia due to diabetes and aging populations presents a challenge that AI and BI can help address by improving treatment planning and resource integration for peripheral artery disease.
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Myocardial bridging (MB) is the most frequent congenital coronary anomaly in which a segment of an epicardial coronary artery takes a tunneled course under a bridge of the myocardium. This segment is compressed during systole, resulting in the so-called "milking effect" at coronary angiography. As coronary blood flow occurs primarily during diastole, the clinical relevance of MB is heterogeneous, being usually considered an asymptomatic bystander.

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Aims: Duchenne muscular dystrophy (DMD) is an X-linked recessive neuromuscular disorder, characterized by significant long-term cardiac involvement. Dilated cardiomyopathy (DCM) is the main cause of death in DMD, and angiotensin-converting enzyme inhibitors (ACEi) and beta-blockers (BB) are first-line treatments in DCM. It is unknown whether angiotensin receptor-neprilysin inhibitor (ARNi) could provide greater benefits in this setting.

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Despite Italy banning use and production of asbestos in 1992, it continues to represent a risk to human health due to its permanence in the places where it was located. The aim of this work is to estimate how many schools in Rome (Italy) have asbestos containing materials (ACM), and to assess whether the location, condition and nature of ACM can influence the level of risk for student health. 3,672 schools were contacted and 1,451 participated to asbestos survey.

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We consider the follow-the-leader approximation of the Aw-Rascle-Zhang (ARZ) model for traffic flow in a multi population formulation. We prove rigorous convergence to weak solutions of the ARZ system in the many particle limit in presence of vacuum. The result is based on uniform BV estimates on the discrete particle velocity.

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