24-28 January 2022

C.E.T. Time

The seminar series is open to everyone

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Register Here

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Program details

January 24

Topic 1: Controversies in Statistical Learning in Clinical Epidemiology

Moderator: Dario Gregori, Professor of Medical Statistics – University of Padova, IT

3:00- 03:20 p.m.

Topic Introduction

Giulia Lorenzoni, Post-Doc Fellow in Clinical Epidemiology – University of Padova, IT

03:20–04:00 p.m.

Controversies in Predictive Modelling, Machine Learning, and Validation in clinical research

Frank Harrell, Professor of Biostatistics – Vanderbilt University, Nashville, TN – USA

04:00–04:40 p.m.

Epidemiologic Opportunities for AI in Abdominal Radiology

Ron Summers, M.D., Ph.D. Senior, Investigator, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory – National Institutes of Health Clinical, Bethesda, MD – USA

04:40–05:20  p.m.

Data science, statistics & health

Rob Tibshirani Professor of Statistics, Professor of Biomedical Data Science – Stanford University, CA – USA

05:20–06:00 p.m

Floor discussion

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January 25

Topic 2: Machine learning perspectives in novel fields of bio-medical research

Moderator: Ileana Baldi, Associate Professor of Medical Statistics – University of Padova, IT

02:00–02:20 p.m.

Topic Introduction

Andrea Ricotti, Medical Intern , Unit of Epidemiology, Regional Health Service, ASL TO3, IT

02:20–03:00 p.m

Machine learning assisted systematic reviews

Corrado Lanera, Assistant Professor in Medical Statistics – University of Padova, IT

03:00–03:40 p.m.

Social Media and other Real World Data for Health-related Research

Graciela Gonzalez-Hernandez, Associate Professor of Informatics – The Perelman School of Medicine, University of Pennsylvania, PA-USA

03:40–04:20 p.m.

Targeted learning with applications to causal inference

Mark van der Laan, Professor of Biostatistics and Statistics – University of California, Berkeley School of Public Health, CA-USA

04:20–05:00 p.m.

Floor discussion

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January 26

Topic 3: “Data” science for “omics” sciences

Moderator: Annibale Biggeri, Professor of Medical Statistics – University of Padova, IT

02:00–02:20 p.m.

Topic Introduction

Luca Vedovelli, Post-Doc Fellow in Biostatistics- University of Padova, IT

02:20–03:00 p.m

Omics technologies for cancer detection and prediction of prognosis 

Giovanna Chiorino, Head, Cancer Genomics Laboratory    

Paola Ostano  Bioinformatician, Cancer Genomics Laboratory  

Fondazione Edo ed Elvo Tempia, Biella, IT  

03:00–03:40 p.m.

Preclinical Proteomics: theory and applications towards translational medicine

Barbara Pioselli and Maria Laura Faietti Senior Research Scientist Preclinical R&D, Analytics and Early Formulations Dept. – Chiesi Farmaceutici , Chiesi, IT

03:40–04:20 p.m.

Metabolomics applications in medical & biological sciences, 

Manuela Simonato, Post Doctoral Fellow in Metabolomics and Mass Spectrometry – Fondazione Istituto di Ricerca Pediatrica Città della Speranza, Padova IT

04:20–05:00 p.m.

Floor discussion

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January 27

Topic 4: Artificial Intelligence in Pathology

Moderator: Annalisa Angelini, Fiorella Calabrese, Professors of Pathology – University of Padova, IT

02:00–02:20 p.m.

Topic Introduction

Onno De Boer, PhD Assistant Professor – Dept. of Pathology Amsterdam University Medical Center, NL

02:20–03:00 p.m

14:20–15:00 Combining artificial intelligence and pathologist assessment for improving diagnosis and research

Gian Kayser, Associate Professor of Pathology – University Medical Center, University of Freiburg, DE

03:00–03:40 p.m.

Technical aspect and quality control in the application of artificial intelligence in pathology

Onno De Boer, PhD Assistant Professor – Dept. of Pathology Amsterdam University Medical Center, NL

03:40–04:20 p.m.

Floor discussion

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January 28

Topic 5: Machine learning and prediction in COVID-19 epidemics

Moderator: Paola Berchialla, Associate Professor of Medical Statistics – University of Torino, IT

02:00–02:20 p.m.

Topic Introduction

Veronica Sciannameo, Post-Doc Fellow in Medical Statistics, University of Torino, IT

02:20–03:00 p.m

Machine learning to improve COVID-19 epidemic behaviour

Danila Azzolina, Assistant Professor in Medical Statistics – University of Ferrara, IT

03:00–03:40 p.m.

Prediction models for diagnosis and prognosis of COVID-19 

Laure Wynants, Assistant Professor of Epidemiology – School for Public Health and Prime Care, Fac. Health, Medicine and Life Sciences, Maastricht University, NL

03:40–04:20 p.m.

“Modelling SARS-CoV-2 transmission in Vo, Italy”  

Ilaria Dorigatti, Lecturer – MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College, London, UK 

04:20–05:00 p.m.

Floor discussion