Animals integrate knowledge about how the state of the environment evolves to choose actions that maximise reward. Such goal-directed behaviour - or model-based (MB) reinforcement learning (RL) - can flexibly adapt choice to changes, being thus disti... read more
Orphan genes - genes lacking detectable homologs outside a species - are widespread in microbial genomes and are thought to contribute to their adaptation and molecular innovation. However, not all predicted orphan genes may represent novel functiona... read more
Speech representations in the human brain do not simply mirror the instantaneous speech signal; rather, they display several properties that are hypothesized to facilitate the integration of speech sounds into words. In particular, neural encodings o... read more
Medication product names in Swiss electronic health records are heterogeneous and often encode multiple attributes (e.g., ingredient, strength, dose form, packaging) in German free text. This limits interoperability and reduces the utility of ATC cod... read more
"Black box" deep learning models for medical image interpretation limit clinical trust and analysis of performance degradation. Here, we introduce Concept-Level Embeddings for Auditable Radiology (CLEAR), an auditable foundation model based on clinic... read more
Background: Integrating advanced artificial intelligence (AI) into clinical decision-support often requires the sharing of sensitive patient data with external services, raising privacy concerns. Homomorphic encryption (HE) allows computing directly ... read more
Skin diseases manifest as visually observable eruption patterns, making image-based assessment a central component of dermatological diagnosis. While recent artificial intelligence (AI)-based approaches have achieved remarkable progress in classifyin... read more
From genome sequencing to single-cell multi-omics profiling, bioinformatic data holds massive promise, calling for data interpretation to facilitate the development of precision medicine with artificial intelligence technologies. Moreover, clinical h... read more
OBJECTIVE: To predict cartilage tumor malignancy from radiographic images combined with readily available non-imaging information based on a vision-language foundation model. MATERIALS AND METHODS: This single-institution study assembled a dataset of... read more
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