Background Heterogeneity in type 2 diabetes presentation and progression suggests that
precision medicine interventions could improve clinical outcomes. We undertook a …

Exploiting existing longitudinal data cohorts can bring enormous benefits to the medical
field, as many diseases have a complex and multi-factorial time-course, and start to develop …

Diabetes Mellitus is a chronic and lifelong disease that incurs a huge burden to healthcare
systems. Its prevalence is on the rise worldwide. Diabetes is more complex than the …

The core idea behind precision medicine is to pinpoint the subpopulations that differ from
one another in terms of disease risk, drug responsiveness, and treatment outcomes due to …

Abstract Purpose of Review With recent advances in the pharmacological management of
type 2 diabetes mellitus (T2DM), there is a growing need to understand which patients …

A central problem in most data-driven personalized medicine scenarios is the estimation of
heterogeneous treatment effects to stratify individuals into subpopulations that differ in their …

Aim To assess the potential of supervised machine‐learning techniques to identify clinical
variables for predicting short‐term and long‐term glycated haemoglobin (HbA1c) response …

Purpose This scoping review summarizes the applications of artificial intelligence (AI) and
bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective …

The last decade has witnessed an exponential growth in the opportunities to collect and link
health‐related data from multiple resources, including primary care, administrative, and …

Background The β-cell function and insulin resistance required by existing methods of
classifying type 2 diabetes are not routinely adopted in most medical institutions of …