QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL. - Kremena V. Star; Quingbin Song; Andy Zhu; Erwin P. Böttinger (Nucleic Acids Res., 2006)

Disease progression subtype discovery from longitudinal EMR data with a majority of missing values and unknown initial time points. - Ilkka Huopaniemi; Girish N. Nadkarni; Rajiv Nadukuru; Vaneet Lotay; Stephen B. Ellis; Omri Gottesman; Erwin P. Bottinger (AMIA, 2014)

Development and validation of an electronic phenotyping algorithm for chronic kidney disease. - Girish N. Nadkarni; Omri Gottesman; James G. Linneman; Herbert S. Chase; Richard L. Berg; Samira Farouk; Vaneet Lotay; Stephen B. Ellis; George Hripcsak; Peggy L. Peissig; Chunhua Weng; Rajiv Nadukuru; et al. (AMIA, 2014)

Leveraging hierarchy in medical codes for predictive modeling. - Anima Singh; Girish N. Nadkarni; John V. Guttag; Erwin P. Bottinger (BCB, 2014)

Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration. - Anima Singh; Girish N. Nadkarni; Omri Gottesman; Stephen B. Ellis; Erwin P. Bottinger; John V. Guttag (J. Biomed. Informatics, 2015)

iGAS: A framework for using electronic intraoperative medical records for genomic discovery. - Matthew A. Levin; Thomas T. Joseph; Janina M. Jeff; Rajiv Nadukuru; Stephen B. Ellis; Erwin P. Bottinger; Eimear E. Kenny (J. Biomed. Informatics, 2017)

HPI-DHC at TREC 2018 Precision Medicine Track. - Michel Oleynik; Erik Faessler; Ariane Morassi Sasso; Arpita Kappattanavar; Benjamin Bergner; Harry Freitas Da Cruz; Jan-Philipp Sachs; Suparno Datta; Erwin P. Böttinger (TREC, 2018)

A Machine Learning Approach for Non-Invasive Diagnosis of Metabolic Syndrome. - Suparno Datta; Anne Schraplau; Harry Freitas Da Cruz; Jan-Philipp Sachs; Frank Mayer; Erwin P. Böttinger (BIBE, 2019)

Qualitative Comparison of Selected Indel Detection Methods for RNA-Seq Data. - Tamara Slosarek; Milena Kraus; Matthieu-P. Schapranow; Erwin P. Böttinger (IWBBIO (1), 2019)

HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population. - Ariane Morassi Sasso; Suparno Datta; Michael Jeitler; Nico Steckhan; Christian S. Kessler; Andreas Michalsen; Bert Arnrich; Erwin P. Böttinger (AIME, 2020)

Event Log Generation in a Health System: A Case Study. - Simon Remy; Luise Pufahl; Jan-Philipp Sachs; Erwin P. Böttinger; Mathias Weske (BPM, 2020)

Position Matters: Sensor Placement for Sitting Posture Classification. - Arpita Mallikarjuna Kappattanavar; Harry Freitas Da Cruz; Bert Arnrich; Erwin P. Böttinger (ICHI, 2020)

Using CEF Digital Service Infrastructures in the Smart4Health Project for the Exchange of Electronic Health Records. - Tamara Slosarek; Attila Wohlbrandt; Erwin P. Böttinger (CoRR, 2020)

StudyU: a platform for designing and conducting innovative digital N-of-1 trials. - Stefan Konigorski; Sarah Wernicke; Tamara Slosarek; Alexander M. Zenner; Nils Strelow; Ferenc D. Ruether; Florian Henschel; Manisha Manaswini; Fabian Pottbäcker; Jonathan A. Edelman; Babajide Alamu Owoyele; Matteo Danieletto; et al. (CoRR, 2020)

A structural variation reference for medical and population genetics. - Ryan L. Collins; Harrison Brand; Konrad J. Karczewski; Xuefang Zhao; Jessica Alföldi; Laurent C. Francioli; Amit V. Khera; Chelsea Lowther; Laura D. Gauthier; Harold Wang; Nicholas A. Watts; Matthew Solomonson; et al. (Nat., 2020)

Unsupervised Learning to Subphenotype Heart Failure Patients from Electronic Health Records. - Melanie Hackl; Suparno Datta; Riccardo Miotto; Erwin P. Böttinger (AIME, 2021)

Domain-Specific Event Abstraction. - Finn Klessascheck; Tom Lichtenstein; Martin Meier; Simon Remy; Jan-Philipp Sachs; Luise Pufahl; Riccardo Miotto; Erwin P. Böttinger; Mathias Weske (BIS, 2021)

Using interpretability approaches to update "black-box" clinical prediction models: an external validation study in nephrology. - Harry Freitas Da Cruz; Boris Pfahringer; Tom Martensen; Frederic Schneider; Alexander Meyer; Erwin P. Böttinger; Matthieu-P. Schapranow (Artif. Intell. Medicine, 2021)

StudyMe: A New Mobile App for User-Centric N-of-1 Trials. - Alexander M. Zenner; Erwin P. Böttinger; Stefan Konigorski (CoRR, 2021)

Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records. - Jessica K. De Freitas; Kipp W. Johnson; Eddye Golden; Girish N. Nadkarni; Joel T. Dudley; Erwin P. Bottinger; Benjamin S. Glicksberg; Riccardo Miotto (Patterns, 2021)

Machine Learning Based Prediction of Incident Cases of Crohn's Disease Using Electronic Health Records from a Large Integrated Health System. - Julian Hugo; Susanne Ibing; Florian Borchert; Jan-Philipp Sachs; Judy Cho; Ryan C. Ungaro; Erwin P. Böttinger (AIME, 2023)

Keyword-optimized Template Insertion for Clinical Information Extraction via Prompt-based Learning. - Eugenia Alleva; Isotta Landi; Leslee J. Shaw; Erwin P. Böttinger; Thomas J. Fuchs; Ipek Ensari (CoRR, 2023)

Core determinants of quality criteria for mhealth for hypertension: evidence from machine learning instruments. - Danielly F. O. de Paula; Ariane Sasso; Justus Cöster; Erwin P. Böttinger (CoRR, 2023)

Comparison of Machine Translation Services in the Biomedical Context. - Tamara Slosarek; Daniel Paeschke; Igor Sivtsev; Erwin P. Böttinger (BIBM, 2024)

Electronic Health Records-based identification of newly diagnosed Crohn's Disease cases. - Susanne Ibing; Julian Hugo; Florian Borchert; Linea Schmidt; Caroline Benson; Allison A. Marshall; Colleen Chasteau; Ujunwa Korie; Diana Paguay; Jan-Philipp Sachs; Bernhard Y. Renard; Judy H. Cho; et al. (Artif. Intell. Medicine, 2025)

Keyword-optimized template insertion for clinical note classification via prompt-based learning. - Eugenia Alleva; Isotta Landi; Leslee J. Shaw; Erwin P. Bottinger; Ipek Ensari; Thomas J. Fuchs (BMC Medical Informatics Decis. Mak., 2025)