Background Research on the integration of artificial intelligence (AI) into community-based
primary health care (CBPHC) has highlighted several advantages and disadvantages in …

Multimorbidity refers to the coexistence of two or more chronic diseases in one person.
Therefore, patients with multimorbidity have multiple and special care needs. However, in …

Multimorbidity—the co-occurrence of multiple diseases—is associated to poor prognosis,
but the scarce knowledge of its development over time hampers the effectiveness of clinical …

Multimorbidity, the presence of 1+ chronic condition in an individual, remains one of the
greatest challenges to health on a global scale. Although the prevalence of multimorbidity …

Objectives Multimorbidity—the co-occurrence of at least two chronic diseases in an
individual—is an important public health challenge in ageing societies. The vast majority of …

Background Multimorbidity is a consequence of both epidemiological and demographic
transition. Unlike comorbidity, it currently has no consensus definition, making it difficult to …

No comprehensive review of Bayesian networks (BNs) in healthcare has been published in
the past, making it difficult to organize the research contributions in the present and identify …

There has been much research effort expended toward the use of Bayesian networks (BNs)
in medical decision-making. However, because of the gap between develo** an accurate …

A bstract A search for pair-produced third generation scalar leptoquarks is presented, using
proton-proton collisions at\(\sqrt {s}= 7\) TeV at the LHC. The data were recorded with the …

The link between pollution and health is commonly explored by trying to identify the
dominant cause of pollution and its most significant effect on health outcomes. The use of …