Despite substantial progress in the study of diabetes, important questions remain about its
comorbidities and clinical heterogeneity. To explore these issues, we develop a framework …

We present a new approach to population health, in which data-driven predictive models are
learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from …

Aims Diabetes is associated with significant pregnancy complications, which can be further
exacerbated by comorbid hypertension. Racial/ethnic differentials in the burden of comorbid …

Background The prevalence of type 2 diabetes (T2DM) is increasing, but increasing
longevity among persons with diagnosed diabetes may be is associated with more …

Identification of individuals at risk of developing disease comorbidities represents an
important task in tackling the growing personal and societal burdens associated with chronic …

Background We sought to examine sex-specific risks for incident cardiovascular disease
(CVD) across the full glycaemic spectrum. Methods Using data from UK Biobank, we …

Background The epidemic of diabetes continues leaving an enormous and growing burden
of chronic disease to public health. This study investigates this growing burden of diabetes …

Importance Spouses share common socioeconomic, environmental, and lifestyle factors,
and multiple studies have found that spousal diabetes status was associated with diabetes …

Objective We build classification models and risk assessment tools for diabetes,
hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We …

Background There is emerging interest in multimorbidity in type 2 diabetes (T2D), which can
be either concordant (T2D related) or discordant (unrelated), as a way of understanding the …