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• W4210804144 abstract "Abstract Current clinical note-taking approaches cannot capture the entirety of information available from patient encounters and detract from patient-clinician interactions. By surveying healthcare providers’ current note-taking practices and attitudes toward new clinical technologies, we developed a patient-centered paradigm for clinical note-taking that makes use of hybrid tablet/keyboard devices and artificial intelligence (AI) technologies. PhenoPad is an intelligent clinical note-taking interface that captures free-form notes and standard phenotypic information via a variety of modalities, including speech and natural language processing techniques, handwriting recognition, and more. The output is unobtrusively presented on mobile devices to clinicians for real-time validation and can be automatically transformed into digital formats that would be compatible with integration into electronic health record systems. Semi-structured interviews and trials in clinical settings rendered positive feedback from both clinicians and patients, demonstrating that AI-enabled clinical note-taking under our design improves ease and breadth of information captured during clinical visits without compromising patient-clinician interactions. We open source a proof-of-concept implementation that can lay the foundation for broader clinical use cases." @default.
• W4210804144 created "2022-02-08" @default.
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• W4210804144 date "2022-01-27" @default.
• W4210804144 modified "2023-10-16" @default.
• W4210804144 title "PhenoPad: Building AI enabled note-taking interfaces for patient encounters" @default.
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• W4210804144 doi "https://doi.org/10.1038/s41746-021-00555-9" @default.
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