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Wed, May 24

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Prediction, classification and causal inference modelling in health data

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Prediction, classification and causal inference modelling in health data
Prediction, classification and causal inference modelling in health data

Time & Location

May 24, 2023, 10:00 AM – 4:00 PM

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Info & Program Details

When

15, 17, 18, 24, 26 May 2023. Two hours at morning and two hours at afternoon.

Price

150 euros students (including PhD, and post-graduate students)

250 euros for academic staff

350 euros for non-academic staff

(IVA esente ai sensi dell’art. 10 DPR 633/72).

Deadline for registration: 10th May 2023

Schedule

Monday (15 May): Probability and conditional independence

Lecture (2 hours, morning)

Probability, random variables, binomial distribution, normal distribution, hypothesis testing,

conditional independence and direct acyclic graphs

Practical session (2 hours, afternoon)

Introduction to R, data simulation and visualization

Wednesday (17 May): Regression modelling and dimension reduction for prediction and

classification

Lecture (2 hours, morning)

Linear regression, logistic regression, model selection, principal component analysis

Practical session (2 hours, afternoon)

Data analysis in R on regression modelling and dimension reduction

Thursday (18 May): Tutorial

Recap of course materials in Week 1, Q&A session (1 hour, morning)

Monday (22 May): Machine learning methods for prediction, classification and model

evaluation

Lecture (2 hours, morning)

Random forest, support vector machine, XGBoost, confusion matrix

Practical session (2 hours, afternoon)

Data analysis in R on prediction, classification and model evaluation using maching learning

methods

Wednesday (24 May): Causal inference

Lecture (2 hours, morning)

Confounding, propensity score, Mendelian randomization

Practical session (2 hours, afternoon)

Data analysis in R on propensity score and Mendelian randomization analysis

Friday (26 May): Seminar talk

Bayesian Mendelian randomization and causal networks (1 hour, morning)

Where?

ONLINE, via Zoom platform.

Teacher

Prof. Hui Guo. University of Manchester

Hui Guo leads the Centre for Biostatistics at the University of Manchester where she has

worked as a Lecturer and then a Senior Lecturer in Biostatistics since 2014. Hui serves on the

University’s management board of the Institute for Data Science and Artificial Intelligence.

She has been a Fellow at The Alan Turing Institute (UK) since 2018. She completed a PhD in

Statistics and worked as a Research Associate at the University of Cambridge. Prior to this,

she obtained her MSc and PG Diploma in Statistics at UCL. Hui’s research focuses on causal

inference in health-related observational studies. Her current work is on exploring causal

mechanisms underlying clinical outcomes from large-scale genetic association data. She is

also interested in genetic and/or biological causal pathways and networks of certain diseases.

Billing

After registering for the course, interested parties will be contacted by the administrative secretariat who will explain the payment methods. The actual registration will be finalized with the payment of the registration fee.

Organizational secretariat:

dott.ssa Gianfranca Corbellini

Phone: 0382 987526

E-mail: gianfranca.corbellini@unipv.it

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