PHARERSS

Application of machine learning and artificial intelligence techniques for medical data analysis of a proteomic study of a cohort of patient with thyroid nodules


05/10/2018
Intervenant(s) : Mattia Garancini (Univ. Milan Bicocca & San Gerardo University Hospital, Italy)
Abstract: This talk will describe a multi-disciplinary effort on the classification of thyroid "undetermined for malignancy" nodules (TIR 3), posing significant issues in the diagnosis of not therapeutic thyroidectomy. The proteomic study of thyroid cells obtained by biopsies that the San Gerardo Hospital (Monza, Italy) and the Milano-Bicocca University are conducting on patients with thyroid nodules represents a novel and promising approach in this sense, but the high volume of proteomic data deriving from the molecular study introduces the challenge of data analysis. The computer science department (LIP6) of Sorbonne Université collaborates in this project by means of the application of machine learning and artificial intelligence techniques for medical data analysis, toward the definition and prototyping of a novel decision support system in the diagnosis and interpretation of thyroid diseases.
Biography: Dr Mattia Garancini is a general surgeon. After graduating on surgical residency from University of Milano-Bicocca, he works in San Gerardo Hospital, Monza (Italy). He has authored more than 50 peer reviewed scientific manuscripts, whose 38 published in international journals with high impact factor. His field of interest include liver, gastrointestinal, colorectal and endocrine surgery. He is an expert in the field of thyroid surgery and a researcher co-investigator of a very selective Italian research grant (AIRC) aimed at identifying molecular markers from medical data useful for the formulation of the most correct surgical indication in patients with thyroid nodules.
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