ICE: Interactive Classification Rule Exploration on Epidemiological Data. - Miro Schleicher; Till Ittermann; Uli Niemann; Henry Völzke; Myra Spiliopoulou (CBMS, 2017)

Predicting the Health Condition of mHealth App Users with Large Differences in the Number of Recorded Observations - Where to Learn from? - Vishnu Unnikrishnan 002; Yash Shah; Miro Schleicher; Mirela Strandzheva; Plamen Dimitrov; Doroteya Velikova; Rüdiger Pryss; Johannes Schobel; Winfried Schlee; Myra Spiliopoulou (DS, 2020)

Active feature acquisition on data streams under feature drift. - Christian Beyer; Maik Büttner; Vishnu Unnikrishnan 002; Miro Schleicher; Eirini Ntoutsi; Myra Spiliopoulou (Ann. des Télécommunications, 2020)

Love thy Neighbours: A Framework for Error-Driven Discovery of Useful Neighbourhoods for One-Step Forecasts on EMA data. - Vishnu Unnikrishnan 002; Yash Shah; Miro Schleicher; Carlos Fernández-Viadero; Mirela Strandzheva; Doroteya Velikova; Plamen Dimitrov; Rüdiger Pryss; Johannes Schobel; Winfried Schlee; Myra Spiliopoulou (CBMS, 2021)

Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus. - Clara Puga; Uli Niemann; Vishnu Unnikrishnan 002; Miro Schleicher; Winfried Schlee; Myra Spiliopoulou (DSAA, 2021)

When Can I Expect the mHealth User to Return? Prediction Meets Time Series with Gaps. - Miro Schleicher; Rüdiger Pryss; Winfried Schlee; Myra Spiliopoulou (AIME, 2022)

Prediction of declining engagement to self-monitoring apps on the example of tinnitus mHealth data. - Miro Schleicher; Sebastian Hamacher; Mats Naujoks; Kolja Günther; Timo Schmidt; Rüdiger Pryss; Johannes Schobel; Winfried Schlee; Myra Spiliopoulou (CBMS, 2022)

Expect the gap: A recommender approach to estimate the absenteeism of self-monitoring mHealth app users. - Miro Schleicher; Rüdiger Pryss; Johannes Schobel; Winfried Schlee; Myra Spiliopoulou (DSAA, 2022)

A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data. - Vishnu Unnikrishnan 002; Miro Schleicher; Clara Puga; Rüdiger Pryss; Carsten Vogel; Winfried Schlee; Myra Spiliopoulou (IDA, 2023)

Prediction meets time series with gaps: User clusters with specific usage behavior patterns. - Miro Schleicher; Vishnu Unnikrishnan 002; Rüdiger Pryss; Johannes Schobel; Winfried Schlee; Myra Spiliopoulou (Artif. Intell. Medicine, 2023)

Predicting User Engagement in mHealth Apps with Neighborhood-based Approaches. - Miro Schleicher; Rüdiger Pryss; Johannes Schobel; Winfried Schlee; Myra Spiliopoulou (CBMS, 2024)

Training and Validating a Treatment Recommender with Partial Verification Evidence. - Vishnu Unnikrishnan 002; Clara Puga; Miro Schleicher; Uli Niemann; Berthold Langguth; Stefan Schoisswohl; Birgit Mazurek; Rilana Cima; Jose Antonio Lopez-Escamez; Dimitrios Kikidis; Eleftheria Vellidou; Rüdiger Pryss; et al. (CoRR, 2024)

Parsimonious predictors for medical decision support: Minimizing the set of questionnaires used for tinnitus outcome prediction. - Miro Schleicher; Petra Brüggemann; Benjamin Böcking; Uli Niemann; Birgit Mazurek; Myra Spiliopoulou (Expert Syst. Appl., 2024)

Training and validating a treatment recommender with partial verification evidence. - Vishnu Unnikrishnan 002; Clara Puga; Miro Schleicher; Uli Niemann; Berthold Langguth; Stefan Schoisswohl; Birgit Mazurek; Rilana Cima; Jose Antonio Lopez-Escamez; Dimitris Kikidis; Eleftheria Vellidou; Rüdiger Pryss; et al. (Artif. Intell. Medicine, 2025)