A Framework for Predicting Impactability of Healthcare Interventions Using Machine Learning Methods, Administrative Claims, Sociodemographic and App Generated Data. - Heather Mattie; Patrick Reidy; Patrik Bachtiger; Emily Lindemer; Mohammad Jouni; Trishan Panch (CoRR, 2019)

Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients. - Antonin Dauvin; Carolina Donado; Patrik Bachtiger; Ke-Chun Huang; Christopher Martin Sauer; Daniele Ramazzotti; Matteo Bonvini; Leo Anthony Celi; Molly J. Douglas (npj Digit. Medicine, 2019)

Belief of having had unconfirmed Covid-19 infection reduces willingness to participate in app-based contact tracing. - Patrik Bachtiger; Alexander Adamson; Jennifer Kathleen Quint; Nicholas S. Peters (npj Digit. Medicine, 2020)

Wearable In-Ear PPG: Detailed Respiratory Variations Enable Classification of COPD. - Harry J. Davies; Patrik Bachtiger; Ian Williams; Philip L. Molyneaux; Nicholas S. Peters; Danilo P. Mandic (IEEE Trans. Biomed. Eng., 2022)

Identifying benefits and concerns with using digital health services during COVID-19: Evidence from a hospital-based patient survey. - Annabelle Painter; Jackie van Dael; Ana Luísa Neves; Patrik Bachtiger; Niki O'brien; Clarissa Gardner; Jennifer Quint; Alexander Adamson; Nicholas Peters; Ara Darzi; Saira Ghafur (Health Informatics J., 2023)

In-ear ECG Signal Enhancement with Denoising Convolutional Autoencoders. - Edoardo Occhipinti; Marek Zylinski; Harry J. Davies; Amir Nassibi; Matteo Bermond; Patrik Bachtiger; Nicholas S. Peters; Danilo P. Mandic (CoRR, 2024)

From ether to ethernet: ensuring ethical policy in digital transformation of waitlist triage for cardiovascular procedures. - Mihir A. Kelshiker; Karanjot Chhatwal; Patrik Bachtiger; Josephine Mansell; Nicholas S. Peters; Daniel B. Kramer (npj Digit. Medicine, 2024)