Di Angelantonio & Ieva Group
In the Di Angelantonio & Ieva Group, epidemiologists, statisticians and data scientists work together to bridge the gap between genotype and phenotype by studying multiple layers of biomolecular data to investigate health from molecules to diseases. To achieve this aim, we develop innovative studies to integrate and link biomolecular data with electronic health records (EHRs), imaging, wearable and other data. We use already available data (e.g. hospital records, prescription records, cohort studies), generate new data from population studies and develop new analytical methods integrated with clinical epidemiology and healthcare research to improve data analysis and interpretation.
By linking molecular and health records, our research will offer major actionable insights into several fields including biology, disease aetiology, risk prediction, early detection, and therapeutic targeting. The methodological approaches we develop will be applied to personalized medicine, with benefits for individual patients’ health, as well as to larger health studies by leveraging the power of large-scale data, with remarkable advances for public health, health data analytics and the development of targeted policy interventions.
Current areas of research include understanding of causal risk factors and development of risk prediction models for non-communicable diseases, using novel analytical approaches to combine different levels of information including omics, genetics and electronic health records.
Group members
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Emanuele Di Angelantonio
Head of Health Data Science Centre -
Francesca Ieva
Associate Head of Research centre -
Laura Bondi
Postdoc -
Solène Cadiou
Postdoc -
Andrea Corbetta
PhD Student -
Nicole Fontana
PhD Student -
Andrea Lampis
PhD Student -
Katherine Marie Logan
PhD Student -
Alessia Mapelli
PhD Student -
Michela Carlotta Massi
Staff Scientist -
Lucia Piubeni
PhD Student -
Carlo Andrea Pivato
Scientific Visitor -
Laura Savarè
Postdoc -
Piercesare Secchi
Scientific Visitor -
Luca Trizio
Scientific Visitor -
Andrea Mario Vergani
PhD Student
Publications
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11/2021 - IEEE
Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification
EEG is a non-invasive powerful system that finds applications in several domains and research areas. Most EEG systems are multi-channel in nature, but multiple channels might include noisy and redundant information and increase computational times of automated EEG decoding algorithms. To reduce the signal-to-noise ratio, improve accuracy and reduce computational time, one may combine channel […]
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11/2021 - Nature Metabolism
Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases
Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1,2,3. Polygenic scores (PGS) aggregate these into a metric representing an individual’s genetic predisposition to disease. PGS have shown promise for early risk prediction4,5,6,7 and there is an open question as to whether PGS can also […]
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10/2021 - IEEE
A Functional Data Analysis Approach to Left Ventricular Remodeling Assessment
Left ventricular remodeling is a mechanism common to various cardiovascular diseases affecting myocardial morphology. It can be often overlooked in clinical practice since the parameters routinely employed in the diagnostic process (e.g., the ejection fraction) mainly focus on evaluating volumetric aspects. Nevertheless, the integration of a quantitative assessment of structural modifications can be pivotal in […]
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08/2021 - Annals of Surgical Oncology volume
Chemotherapy-Associated Liver Injuries: Unmet Needs and New Insights for Surgical Oncologists