Beating the Noise: New Statistical Methods for Detecting Signals in MALDI-TOF Spectra Below Noise Level. - Tim O. F. Conrad; Alexander B. Leichtle; Andre Hagehülsmann; Elmar Diederichs; Sven Baumann; Joachim Thiery; Christof Schütte (CompLife, 2006)

Sparse Proteomics Analysis - a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data. - Tim O. F. Conrad; Martin Genzel; Nada Cvetkovic; Niklas Wulkow; Alexander B. Leichtle; Jan Vybíral; Gitta Kutyniok; Christof Schütte (BMC Bioinform., 2017)

A comparative study of pattern recognition algorithms for predicting the inpatient mortality risk using routine laboratory measurements. - Narayan Schütz; Alexander B. Leichtle; Kaspar Riesen (Artif. Intell. Rev., 2019)

SPHN/PHRT - MedCo in Action: Empowering the Swiss Molecular Tumor Board with Privacy-Preserving and Real-Time Patient Discovery. - Jean Louis Raisaro; Juan Ramón Troncoso-Pastoriza; Sylvain Pradervand; Michel A. Cuendet; Mickaël Misbach; João Sá Sousa; Francesco Marino; Nicolas Freundler; Nicolas Rosat; David Cavin; Alexander B. Leichtle; Jacques Fellay; et al. (MIE, 2020)

Classification of oncology treatment responses from radiology reports with supervised machine learning. - Luc Mottin; Jean-Philippe Goldman; Christoph Jäggli; Rita Achermann; Julien Gobeill; Julien Knafou; Julien Ehrsam; Alexandre Wicky; Camille L. Gerard; Tanja Schwenk; Mélinda Charrier; Petros Tsantoulis; et al. (AMIA, 2022)

Multilingual RECIST classification of radiology reports using supervised learning. - Luc Mottin; Jean-Philippe Goldman; Christoph Jäggli; Rita Achermann; Julien Gobeill; Julien Knafou; Julien Ehrsam; Alexandre Wicky; Camille L. Gerard; Tanja Schwenk; Mélinda Charrier; Petros Tsantoulis; et al. (Frontiers Digit. Health, 2023)