Publications by authors named "L M Christmann"
Making health data available for secondary use enables innovative data-driven medical research. Since modern machine learning (ML) methods and precision medicine require extensive amounts of data covering most of the standard and edge cases, it is essential to initially acquire large datasets. This can typically only be achieved by integrating different datasets from various sources and sharing data across sites.
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- Risk stratification is essential for identifying high-risk individuals and preventing diseases, and this study investigated using NMR spectroscopy-derived metabolomic profiles to assess risk for 24 common diseases, potentially improving beyond traditional clinical predictors.
- A neural network was trained on data from nearly 118,000 participants, successfully linking metabolomic states to incident disease rates for most conditions studied, except breast cancer.
- The findings indicate that combining metabolomic states with demographic factors like age and sex can enhance predictions for several common diseases, proving clinically useful across different decision thresholds.
Background: In primary cardiovascular disease prevention, early identification of high-risk individuals is crucial. Genetic information allows for the stratification of genetic predispositions and lifetime risk of cardiovascular disease. However, towards clinical application, the added value over clinical predictors later in life is crucial.
View Article and Find Full Text PDFObjective: To determine whether plasma concentrations of bone turnover markers in growing Hanoverian foals are influenced by age, housing conditions, or osteochondrosis.
Animals: 165 healthy foals and 119 foals with osteochondrosis.
Procedures: Foals were allocated according to birth date and housing management into groups of early-born (born before March 31, 2001; n = 154 foals, 88 of which were healthy and 66 of which had osteochondrosis) and late-born (born after March 31, 2001; 130 foals, 77 of which were healthy and 53 of which had osteochondrosis) foals.