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Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.

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The origins and prehistory of domestic sheep () are incompletely understood; to address this, we generated data from 118 ancient genomes spanning 12,000 years sampled from across Eurasia. Genomes from Central Türkiye ~8000 BCE are genetically proximal to the domestic origins of sheep but do not fully explain the ancestry of later populations, suggesting a mosaic of wild ancestries. Genomic signatures indicate selection by ancient herders for pigmentation patterns, hornedness, and growth rate.

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Background Many people with traumatic brain injury (TBI) report problems with social functioning that can have immediate and enduring impacts. We aimed to explore perceptions of social functioning after TBI and understand attitudes towards medication that could improve long-term social outcomes. Method A qualitative descriptive approach using interview methods was conducted in Victoria, Australia.

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A model of care redesign within rheumatology: A mixed methods approach integrating nurse practitioners and physician assistants.

J Am Assoc Nurse Pract

January 2025

Division of Cardiology, Department of Medicine, Duke Health Integrated Practice, Duke University Health System, Durham, North Carolina.

Background: Increasing patient demand and clinician burnout in rheumatology practices have highlighted the need for more efficient models of care (MOC). Interprofessional collaboration is essential for improving patient outcomes and clinician satisfaction.

Local Problem: Our current MOC lacks standardization and formal integration of Nurse Practitioners (NPs) and Physician Assistants (PAs), resulting in reduced clinician satisfaction and limited patient access.

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Retrosynthesis is a strategy to analyze the synthetic routes for target molecules in medicinal chemistry. However, traditional retrosynthesis predictions performed by chemists and rule-based expert systems struggle to adapt to the vast chemical space of real-world scenarios. Artificial intelligence (AI) has revolutionized retrosynthesis prediction in recent decades, significantly increasing the accuracy and diversity of predictions for target compounds.

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