Wednesday 25th September, 11.30am – 13.00pm

Europe Hall – CNR-IRPPS

The author, Alexander Mulieri, will dialogue with Daniele Archibugi, Gianni Cuperlo, Maria Grasso e Tommaso Visone.

7 March 2024 – h. 8.30

Sala Marconi - CNR Piazzale Aldo Moro 7 - Rome

Download the program in pdf. 
Read the description of the event on the portal CNR.

9 October 2023 – h. 10.00

Sala Europa, IRPPS via Palestro 32 – Rome

Abstract

Artificial Intelligence (AI) is transforming people's lives in unprecedented ways. AI models have human or superhuman abilities in multiple tasks, eg, gaming, driving, conversation, and content organization. In biomedical research, however, AI demonstrated as much promise, eg, in molecular drug design, as much disappointment, eg, in clinical drug repurposing or public health intervention. One of the reasons is that the datasets AI feeds on – sourced from real world databases such electronic health records (EHR) – are often littered with bias. Such bias might be irrelevant to predict the happening of health conditions, but it influences any strategy to prevent such conditions from happening. In this talk, we will take a dive into the promises and perils of AI in healthcare, and its troubled relationship with data, bias, and causality. We will explore novel causal AI methodologies able to both provide accurate individual health predictions as well as interventions. Finally, we will present use cases of causal AI on large, integrated EHR data, and an eagle's view of EHR consortia in the USA.

Short biographies

Mattia Prosperi, PhD, FAMIA, is Professor in the Department of Epidemiology, and Associate Dean of AI and Innovation in the College of Public Health and Health Profession at University of Florida. His background is in computer science engineering, with expertise in machine learning, bio-health informatics, and epidemiology. His research leverages technology and data intelligence to develop prediction and intervention models for improving future health and lives. In his administrative role di lui, his mission di lui is to expand AI infrastructure, training, research and expertise capacity in public health and health professions.

Yi Guo, PhD, is Associate Professor in the Department of Health Outcomes, Policy and Biomedical Informatics, College of Medicine, University of Florida. He has a multi-disciplinary background in the analysis of real-world data, including electronic health records and administrative claims, experimental and observational study design, predictive modeling (eg, statistical and machine learning), causal modeling, and analysis of patient-reported outcomes in clinical and public health applications, and among various populations, especially vulnerable populations.

Note CNR - IRPPS

Interviews with Antonio Tintori

Interviews with Giulia Ciancimino

Participants

CNR Press Office: Emanuele Guerrini 

Technical Manager: Marco Ferrazzoli

Secretariat: Press office

Research Institute on Population and Social Policy of the National Research Council (Cnr-Irpps) conducted two studies in primary schools in Rome e in upper secondary schools in Italy showing the presence of a pronounced adherence to stereotyped roles in boys and girls and the attenuation of these conditioning in the transition to adolescence.

The data indicate such gaps and stereotypes reproduce still strongly in the family environmentand the important role of the school in countering them.

Three graphs are presented below to view the results.

• Figure 1. Level of adherence to male and female stereotyped roles 
  (answers for children and adolescents):

• Figure 2. Men are more likely to:

• Figure 3. Women are more likely to: