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Lehmann, Vera 
ORCID: https://orcid.org/0000-0002-6038-809X; Zueger, Thomas ORCID: https://orcid.org/0000-0001-6190-7405; Maritsch, Martin ORCID: https://orcid.org/0000-0001-9920-0587; Notter, Michael ORCID: https://orcid.org/0009-0002-8404-570X; Schallmoser, Simon ORCID: https://orcid.org/0000-0003-4076-0584; Bérubé, Caterina ORCID: https://orcid.org/0000-0001-5247-8485; Albrecht, Caroline ORCID: https://orcid.org/0009-0001-3669-0192; Kraus, Mathias ORCID: https://orcid.org/0000-0002-2021-2743; Feuerriegel, Stefan ORCID: https://orcid.org/0000-0001-7856-8729; Fleisch, Elgar ORCID: https://orcid.org/0000-0002-4842-1117; Kowatsch, Tobias ORCID: https://orcid.org/0000-0001-5939-4145; Lagger, Sophie ORCID: https://orcid.org/0009-0004-5313-7518; Laimer, Markus ORCID: https://orcid.org/0000-0002-7622-0822; Wortmann, Felix ORCID: https://orcid.org/0000-0001-5034-2023 und Stettler, Christoph ORCID: https://orcid.org/0000-0003-1691-6059
(2024):
Machine Learning to Infer a Health State Using Biomedical Signals — Detection of Hypoglycemia in People with Diabetes while Driving Real Cars.
In: NEJM AI, Bd. 1, Nr. 3
[PDF, 524kB]
ORCID: https://orcid.org/0000-0002-6038-809X; Zueger, Thomas ORCID: https://orcid.org/0000-0001-6190-7405; Maritsch, Martin ORCID: https://orcid.org/0000-0001-9920-0587; Notter, Michael ORCID: https://orcid.org/0009-0002-8404-570X; Schallmoser, Simon ORCID: https://orcid.org/0000-0003-4076-0584; Bérubé, Caterina ORCID: https://orcid.org/0000-0001-5247-8485; Albrecht, Caroline ORCID: https://orcid.org/0009-0001-3669-0192; Kraus, Mathias ORCID: https://orcid.org/0000-0002-2021-2743; Feuerriegel, Stefan ORCID: https://orcid.org/0000-0001-7856-8729; Fleisch, Elgar ORCID: https://orcid.org/0000-0002-4842-1117; Kowatsch, Tobias ORCID: https://orcid.org/0000-0001-5939-4145; Lagger, Sophie ORCID: https://orcid.org/0009-0004-5313-7518; Laimer, Markus ORCID: https://orcid.org/0000-0002-7622-0822; Wortmann, Felix ORCID: https://orcid.org/0000-0001-5034-2023 und Stettler, Christoph ORCID: https://orcid.org/0000-0003-1691-6059
(2024):
Machine Learning to Infer a Health State Using Biomedical Signals — Detection of Hypoglycemia in People with Diabetes while Driving Real Cars.
In: NEJM AI, Bd. 1, Nr. 3
[PDF, 524kB]
Schallmoser, Simon ORCID: https://orcid.org/0000-0003-4076-0584; Zueger, Thomas ORCID: https://orcid.org/0000-0001-6190-7405; Kraus, Mathias ORCID: https://orcid.org/0000-0002-2021-2743; Saar-Tsechansky, Maytal ORCID: https://orcid.org/0000-0002-2400-3762; Stettler, Christoph ORCID: https://orcid.org/0000-0003-1691-6059 und Feuerriegel, Stefan ORCID: https://orcid.org/0000-0001-7856-8729
(2023):
Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study.
In: Journal of Medical Internet Research, Bd. 25, e42181
ORCID: https://orcid.org/0000-0003-4076-0584; Zueger, Thomas ORCID: https://orcid.org/0000-0001-6190-7405; Kraus, Mathias ORCID: https://orcid.org/0000-0002-2021-2743; Saar-Tsechansky, Maytal ORCID: https://orcid.org/0000-0002-2400-3762; Stettler, Christoph ORCID: https://orcid.org/0000-0003-1691-6059 und Feuerriegel, Stefan ORCID: https://orcid.org/0000-0001-7856-8729
(2023):
Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study.
In: Journal of Medical Internet Research, Bd. 25, e42181
Zueger, Thomas ORCID: https://orcid.org/0000-0001-6190-7405; Schallmoser, Simon; Kraus, Mathias; Saar-Tsechansky, Maytal; Feuerriegel, Stefan ORCID: https://orcid.org/0000-0001-7856-8729 und Stettler, Christoph
(2022):
Machine Learning for Predicting the Risk of Transition from Prediabetes to Diabetes.
In: Diabetes Technology & Therapeutics, Bd. 24, Nr. 11: S. 842-847
ORCID: https://orcid.org/0000-0001-6190-7405; Schallmoser, Simon; Kraus, Mathias; Saar-Tsechansky, Maytal; Feuerriegel, Stefan ORCID: https://orcid.org/0000-0001-7856-8729 und Stettler, Christoph
(2022):
Machine Learning for Predicting the Risk of Transition from Prediabetes to Diabetes.
In: Diabetes Technology & Therapeutics, Bd. 24, Nr. 11: S. 842-847
Schallmoser, Simon; Krippendorf, Sven; Chadha-Day, Francesca und Weller, Jochen ORCID: https://orcid.org/0000-0002-8282-2010
(2022):
Updated bounds on axion-like particles from X-ray observations.
In: Monthly Notices of the Royal Astronomical Society, Bd. 514, Nr. 1: S. 329-341
ORCID: https://orcid.org/0000-0002-8282-2010
(2022):
Updated bounds on axion-like particles from X-ray observations.
In: Monthly Notices of the Royal Astronomical Society, Bd. 514, Nr. 1: S. 329-341