Making sensitive data reusable through synthetic data generation

By analysing the metabolism using big data techniques, we can identify health risks at an earlier stage. Thomas Hankemeier, professor of Analytical Biosciences at the Leiden Academic Centre for Drug Research, explains how that works.

This monograph focuses on clustering of objects in high-dimensional data, given the restriction that the objects do not cluster on all the attributes, not even on a single subset of attributes, but often on different subsets of attributes in the data.

VODAN Africa started as a platform to enable access to critical data needed from Africa to fight the novel COVID-19. The initiative was inspired by the experience from the Liberia Ebola Virus outbreak in 2014: early detection requires contact tracing. Inclusion of the most vulnerable is critical to…

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

How can interdisciplinary and transdisciplinary collaborations between psychology and public administration contribute to the development and application of behavioural insights that improve government functioning and its interaction with citizens?

Machine Learning is becoming a more and more substantial technology for industry.

Promotor: J.N. Kok, Co-promotor: F.J. Verbeek

The aim of this project is to develop accurate but interpretable ensemble learning methods for high-dimensional multi-domain data.

In Luganda, the widest spoken minority language in East African country Uganda, the word for photographs is Ebifananyi. However, ebifananyi does not, contrary to the etymology of the word photographs, relate to light writings. Ebifananyi instead means things that look like something else. Ebifananyi…

Governments have increasing amounts of data at their disposal. How can big data be used in policymaking? And are governments ready to deal with all this data? That is what Sarah Giest, Assistant Professor at the Institute of Public Administration, is interested in.

Promotor: Prof.dr. B.R. Katzy, Co-promotor: R. Ortt

How to strike a balance between the sometimes conflicting stakes of individual, public and private data-producers and data-processors?

The deeper understanding of an organism's pathology is important for developing treatments. Over centuries of systematic research, clinical researchers have demonstrated that the more information they acquire about the cellular properties and their organisation in the tissue, the better they can understand…

Generally the data from remote sensing surveys - the scanning of the earth by satellite or aircraft in order to obtain information about it - is screened manually in archaeology. However, constant monitoring of the earth's surface causes a huge influx of data of high complexity and high quality. To…

This project aims to develop advanced data analysis methods for monitoring and increasing our understanding on biodiversity dynamics in nature reserves such as the Oostvaardersplassen.

This project’s aim is to critically assess current homicide data sources in order to develop a proposal for long-term EU-level monitoring of DRH.

The RISIS project aims at creating a distributed research infrastructure to support and advance science and innovation studies. This will give the field a strong scientific push forward, and at the same time, provide a radically improved evidence base for research and innovation policies, for research…

Sport Data Center

Patients share valuable advice and experiences with their peers in online patient discussion groups.

Promotor: A.P.IJzerman Co-promotor: A. Bender

While bioinformatics methods deal with the analysis of sequence information (be it proteins or DNA), the field of cheminformatics is concerned with the analysis of small-molecule datasets.

This project aims to improve understanding of, and responses to, the phenomenon of lone actors through analysis of comprehensive data on cases from across Europe.

Data science offers exciting new instruments for governments to reach out to citizens, for example by using data-driven information channels, providing real-time simulations, or personalizing services based on citizen data. At the same time, the possibilities and use of data science methods can have…

This thesis focuses on the social dimensions of crane and wetland conservation in rural landscapes in Kenya, Uganda and Zimbabwe.

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

The goal is to establish an intuitive search and querying service that allows researchers to quickly retrieve the most valuable digital resources, in order to allow them to integrate and synthesise the results into a coherent narrative of the past. The current focus of the project is to implement…

Welcome to the news hub of the Master’s program in Health, Ageing, and Society at LUMC. In this section, you'll find the latest updates and articles about the program, covering a wide range of topics, from key achievements and milestones to insightful perspectives and recent developments. Articles are…

Latest technological developments in data mining and profiling.

Indigenous Latin American artifacts have attracted the interest of Europeans since the earliest moment of contact between Europeans and the Indigenous peoples of the Americas. The ERC-funded BECACO project uses an innovative multidisciplinary framework to investigate the provenance of ethnographic and…

With the rise of information and communication technologies, large amounts of data are being generated and stored in databases. In order to get a better grip on these large amounts of data, serious efforts are being made to discover patterns and relations in the data with the help of new techniques.…

Quantifying physical activity (using accelerometers) and combining the frequency and intensity of activities with health data (brain MRI, traditional clinical parameters and metabolomics) is of utmost importance to monitor mobility and health among older individuals and study health promotion during…

This work describes several studies into the electroreduction of carbon dioxide (CO2RR), both regarding mechanistical aspects and catalyst stability considerations. Mechanistic insights into carbon-carbon bond formation on a silver catalyst are described in Ch 2, were we find an acetaldehyde-like surface…