Medical Image Classification with Vision Transformers

Vision Transformers can outperform other methods like RNNs in classification tasks in the medical domain. MedMNIST (v2) is a collection of biomedical images, and contains eight 2D image datasets for a multi-class classification task. Using a pre-trained Vision Transformer model, and fine-tuning it for each dataset, we were able to outperform almost all of the … Read more

Sentiments about Mental Health on Twitter – Before and during the COVID-19 Pandemic

The COVID-19 pandemic not only affected the respiratory system, but, together with measures like social distancing, potentially affected the mental health of millions of people. What do Twitter (X) users talk about when they talk about #MentalHealth and #Depression? Did it change through the pandemic? We collected almost 3,000,000 tweets from more than 300,000 Twitter … Read more

Mobile Sensing in Personality Science

How can mobile sensing, using the smartphone’s sensors for recording and storing data, help in personality science? Read our comprehensive book chapter on this topic. We cover an overview of related work and show the differences in researching personality traits vs. personality states with mobile sensing. We showcase a concrete mobile-sensing application and provide a … Read more

Presentation at IEEE EMBS event

Today, I gave a presentation at an IEEE EMBS (Engineering in Medicine and Biology Society) event. My talk was about Predicting Adherence to Ecological Momentary Assessments, and I presented our findings about the predictability of users of a smartphone app filling out questionnaires. Based on smartphone sensor data, we utilized machine learning to try to … Read more

Self-Assessment of Having COVID-19 With the Corona Check mHealth App

At the beginning of the COVID-19 pandemic, with a lack of knowledge about the novel virus and a lack of widely available tests, getting first feedback about being infected was not easy. To support all citizens in this respect, we developed the mobile health app Corona Check. Based on a self-reported questionnaire about symptoms and … Read more

Social Media App Usage in Relation with PHQ-9 Depression Scores during the COVID-19 Pandemic

With about 300 million affected people, major depressive disorder (MDD) is one of the most common diseases worldwide. During the COVID-19 pandemic, the number of cases increased even further, by 28%. Many factors may be correlated with MDD, including the excessive use of social media apps. We investigated the relationship between the use of social … Read more

Porn Addiction Relapse Prediction

Can you predict if a self-described pornography-addict will relapse – based on his previous mental condition? We used machine learning to answer this question based on data collected by polish collaborators. Users used a mobile app for tracking their addictions and mental state. You can find a full project description and code on GitHub.

National Institute of Informatics (NII), Tokyo, Japan

Today, I am starting at the National Institute of Informatics (NII) in the group of Prof. Akiko Aizawa. I acquired funding financing my full-time position in the competitive program IFI (German: Internationale Forschungsaufenthalte für Informatikerinnen & Informatiker) by the German Academic Exchange Service (DAAD). I will work on topics relating to user retention, data science, … Read more

WhatsNextApp: LSTM-Based Next-App Prediction With App Usage Sequences

Next app prediction can help enhance user interface design, pre-loading of apps, and network optimizations. Prior work has explored this topic, utilizing multiple different approaches but challenges like the user cold-start problem, data sparsity, and privacy concerns related to contextual data like location histories, persist. The user cold-start problem occurs when a user has recently … Read more