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Integration and usability of a digital cancer risk stratification tool to optimize identification of patients at risk for hereditary cancers: A pilot study
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education model focuses cultivation students creativity practical ability integration maker education development artificial intelligence great significance order analyze study application effect artificial intelligence maker education based study adopts method questionnaire case analysis investigate analyze students three dimensions learning experience learning attitude learning emotion learning effect transfer survey results show whole integration artificial intelligence technology maker education significantly improve students learning feelings attitudes enhance enthusiasm learning emotions research also finds positive impact students learning effect transfer ability learning experience learning attitude learning emotion learning effect learning transfer related gender teaching time teaching subjects majors therefore article suggest creating maker cultural atmosphere creating maker resource space improving maker education system provides valuable reference promoting development maker education courses field artificial intelligence