Contacts

Office: UPIT – Unità Per l’Innovazione Tecnologica
2nd Floor, Polo didattico cravino, segreterie cravino entrance;
Department of Electrical, Computer and Biomedical Engineering,
University of Pavia
Via Ferrata 5 27100 Pavia (Italy)

Tel: +39-0382-98 5981
Fax: +39-0382-98 5060
E-Mail: arianna dot dagliati at unipv dot it

Biopic

Arianna Dagliati is Assistant Professor (RTDa) at the Department of industrial and information engineering, The University of Pavia (Italy).

Her research is dedicated to the development of mining approaches for enabling the recognition of temporal patterns and electronic phenotypes in longitudinal clinical data.

Her commitment is to align her work to global translational medicine research priorities, embrace key steps for providing direct impact of machine learning and artificial intelligence in clinical practice: from software tools that link clinical knowledge with machine learning-based evidences from longitudinal data, to modelling approaches to identify critical transitions in patient’s histories.

She has an extensive history of working in multidisciplinary teams and collaborated with a broad range of administrative, specialist and generalist clinicians, and public health professionals, to deliver scientific findings and to integrate algorithms in clinical decision support systems.

She is part of the 4CE international consortium for electronic health record data-driven studies of the COVID-19 pandemic and appointed as AIME (society of AI in medicine) Board Member.

Consulting hours

Student consulting times: by appointment (e-mail)

Current Position

Assistant Professor (RTDa), Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy

Education

International and National Organizations, Awards

4CE international consortium for electronic health record data-driven studies of the COVID-19 pandemic

AIME Board Member

Research Projects

Research Projects

Publication list

Author of about 40 scientific publications

My page on Google Scholar

Bibliometric indices

Citations825731
h-index1615
i10-index2623


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