CV

Data Scientist

I am currently working on data standardisation and development of prediction models to inform trials at the intensive care unit.

Postdoctoral researcher

Building on previous work, I worked on the development of DL models for cancer detection and the integration of new data modalities.

Visiting researcher

This experience was part of the change of research environment of my PhD. In this period I visited Chris Sander's lab in Boston, continuing working on pancreatic cancer prediction. In particular, the aim of my visit was testing the generalizability of the model trained on the Danish data on a US dataset. To accomplish this, I had to deploy the ML model on a new cloud, Google cloud platform, and develop a new pipeline for the data preprocessing.

Research assistant and PhD

In this period I conducted research at the Novo Nordisk Center for Protein Research. I have been actively working on various projects encompassing machine learning applications on diverse and unique datasets, including registries, electronic health records and medical images. Notably, I worked on the development of models for early detection of pancreatic cancer using patients' disease history from the Danish registries. I also worked on the development of a decision support tool for detecting clinical deterioration using EHR collected in the general depertments. Other projects involved survival analysis in the ICU and pharmacovigilance using NLP techniques.

Research master student

This research project was part of my master thesis. In this period my task was to try improving current mortality risk models in the intensive care unit (ICU). In particular, I worked on time-series collected by monitors in the ICU to enhance an LSTM model using hand-crafted features from high-frequency data.

Development of a dynamic prediction model for unplanned ICU admission and mortality in hospitalized patients

PLOS digital health

Placido D, Thorsen-Meyer H-C, Kaas-Hansen BS, Reguant R, Brunak S.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories

Nature Medicine

Placido D, Yuan B, Hjaltelin JX, Zheng C, ..., Brunak S, Sander C

Discrete-time survival analysis in the critically ill: a deep learning approach using heterogeneous data

Nature digitial medicine

Thorsen-Meyer HC, Placido D, Kaas-Hansen B.S, Nielsen AP, .. Perner A, Brunak S

Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records

Basic and Clinical Pharmacology and Toxicology

Benjamin Skov Kaas‐Hansen, Davide Placido, Cristina Leal Rodríguez, ..., Stig Ejdrup Andersen

PhD

University of Copenhagen

Bioinformatics and Biostatistics

Master degree

Polytechnic University of Turin

Biomedical engineering

Bachelor degree

Polytechnic University of Turin

Biomedical engineering