The "School of Rock" (SOR) expedition was carried out onboard the JOIDES Resolution during a 2 wk transit from Victoria, British Columbia, Canada, to Acapulco, Mexico, in 2005 as a pilot field program to mak...
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The article reviews two books related to moral education including 'Happiness and education' and 'Critical lessons: what our schools should teach,' by Nel Noddings.
The article reviews two books related to moral education including 'Happiness and education' and 'Critical lessons: what our schools should teach,' by Nel Noddings.
The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and ...
The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma. Yuan and colleagues developed an artificial intelligence-based method to derive growth patterns and morphological features from hematoxylin and eosin-stained slides of lung adenocarcinoma samples, for improved tumor grading and patient prognostication.
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