Dear students, since the LIACS matching meetup in October 2024, we have already teamed up with 4 new master students for our thesis topics, so we cannot take on more new students in the coming months. Check back in 2025 for more opportunities! Cheers, Marco
[ML] Balanced and balancing distance measures for mixed variable types
Many AI, ML and data science methods depend on the notion of a distance, which often acts as a dissimilarity measure between observations in the data set. In real-world data sets, variables have various types, e.g. continuous, ordinal, nominal/categorical and binary, contained within one data set. In such cases, dissimilarity is almost always measured using Gower's distance. It min-max-scales numeric variables, and assigns distances to non-numeric variables as 1 if the values are unequal, and 0 if they are. Dimensions are just added directly, like in the Manhattan distance measure. The implication is that distances are dominated by categorical dimensions, as the distance (if non-zero) corresponds to the largest possible distance in the numeric dimensions, which will typically have smaller values. Also, average distances per dimension are not equalized (not even if the dimensions themselves are normalized or standardized first), and are dominated by imbalanced columns. This project will develop a balanced version of Gower's distance that makes the contribution of every feature on average equal, and leaves the possibility to re-weigh the contribution of features. The resulting distance measure will be used for risk stratification of people with metabolic syndrome on a large scale data warehouse with health, demographic and socio-economic data, but is expected to find wide-spread use in distance-based machine learning tasks on heterogeneous data.
Daily supervisor: Marcel Haas (LUMC), Marco Spruit[ML] MDL-based association rule mining on ELAN data
Further the research in MSc thesis bySince the 1990s, there has been a rapid increase in overuse, abuse, and overdose deaths, along with the significant medical, social, psychological, demographic, and economic consequences associated with prescription opioids. Social and psychological effects are of particular interest because they extend beyond individual addiction to impact families, communities, and social systems, leading to issues such as mental health disorders, social isolation, and economic hardship. In this work, association rule mining is used on the ATC, ICPC codes, and patient demographics to draw interesting relationships. Specifically, Apriori and FP-growth algorithms were used to find frequent itemsets from which association rules were derived.
Daily supervisor: Marco Spruit, t.b.d.
[NLP] LLMs in Dutch Elderly Care
The MINUTES study: The aim of the COVID-19 management in nursing homes by outbreak teams (MINUTES) study is to describe the challenges, responses and the impact of the COVID-19 pandemic in Dutch nursing homes. In this first article, we describe the MINUTES Study and present data characteristics.
The MINUTES study has been very valuable in managing the crisis in nursing homes, due to the COVID-19 pandemic. Data, minutes of crisis-team meetings, were gathered and analysed using traditional qualitative research methods. In total, more than 10.000 separate minutes have been collected.
The RQ that we are interested in, is:
[NLP] LLMs in the analysis of interviews with older people about goals of care: a pilot study
Large language models such as used in ChatGPT and chatbots are a form of conversational artificial intelligence. Qualitative research using interviews and focus groups use analysis of conversations to identify themes or paradigms.
Especially in the care for older people conversations regarding goals, qualitative research plays an important goal as older people have care needs that may be different that younger adults. These qualitative interview studies are, however, time consuming and it is unknown what role LLMs may play.
Our objective is to compare the results of the qualitative analysis of single interviews performed according to current standards with the analysis performed by LLMs.
Methods: As a part of the Master Health Ageing and Society, ten groups of four students will perform interviews with older people about the perspective on life and care. The interviews are transcribed ad verbatim, coded using atlas.ti software and an inductive analysis will be performed too.
In parallel, taking the interview transcripts will be analyzed by LLMs with prompts to analyze with the same intention using different prompts and LLMs.
Results of the conventional analysis and analysis by LLMs will be compared. Interviewees will be asked to blindly score all of the analyses (scale of 1 to 10) on how good it reflects the their perspective and to indicate which of the four analyses performed best.