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Abstract Structural brain alterations associated with depression and anxiety are subtle, heterogeneous, and difficult to characterize. We applied autoencoder-based normative modeling to contrastively learned structural MRI representations from two large population-based cohorts (German National Cohort, N ≈ 29,000; UK Biobank, N ≈ 25,000) to quantify individual deviations from normative brain structure across symptom dimensions of depression, anxiety, and, for contextualization, alcohol use.
Vermutlich gibt es wenige technologische Debatten, die so stark polarisieren wie das Thema Künstliche Intelligenz (KI). Die Skala reicht von utopischen Idealen, in denen uns Maschinen von mühseliger Erwerbsarbeit befreien, bis zu dystopischen Sorgen, in denen Menschen überflüssig werden. Auch die Popkultur trägt zu diesen Vorstellungen bei. Daher ist es höchste Zeit, die derzeitigen Entwicklungen sachlich einzuordnen.
Pneumonia is considered to be one of the leading causes of death worldwide. The outcome depends on both, proper antibiotic treatment and the effectivity of the immune response of the host. However, due to the complexity of the immunologic cascade initiated during infection, the latter cannot be predicted easily. We construct a biomathematical model of the murine immune response during infection with pneumococcus aiming at predicting the outcome of antibiotic treatment.
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