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Register a new userThe Biomaterials Annotator: a system for ontology-based concept annotation of biomaterials text
The Biomatials Annetator: نظام التعليق التوضيحي المفهوم القائم على الأطباء
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المواد الحيوية هي المواد الاصطناعية أو الطبيعية المستخدمة لبناء الأعضاء الاصطناعية، أو تصنيع الأطراف الاصطناعية، أو استبدال الأنسجة. شهد القرن الماضي تطور الآلاف من المواد الحيوية الجديدة، ونتيجة لذلك، زيادة أسية في المنشورات العلمية في هذا المجال. يمكن أن تمكن تحليل واسع النطاق من المواد الحيوية وأدائها اختيار المواد التي يحركها البيانات وتصميم الزرع. ومع ذلك، يتطلب مثل هذا التحليل تحديد وتنظيم المفاهيم، مثل المواد والهياكل، من النصوص المنشورة. لتسهيل استخراج المعلومات في المستقبل وتطبيق تقنيات تعلم الآلات، قمنا بتطوير Annotator الدلالي خصيصا مصممة خصيصا لأدبيات المواد الحيوية. تم تنفيذ Annetator SNANTATATATATATOR باتباع منظمة وحدات تستخدم حاويات البرمجيات للمكونات المختلفة وتزويرها باستخدام nextflow كدير سير العمل. تم تطوير مكونات معالجة اللغة الطبيعية (NLP) بشكل أساسي في Java. سمح هذا الإعداد بالاعتراف الكي في الكيان المسمى بدقة سبعة عشر فئة ذات صلة بمجال المواد الحيوية. نحن هنا تفصيل تطوير وتقييم وأداء النظام، وكذلك إصدار المجموعة الأولى من ملخصات المواد الحيوية المشروحة. نجعل كل من الجور والنظام المتاح للمجتمع لتعزيز الجهود المستقبلية في هذا المجال والمساهمة في استدامتها.
Biomaterials are synthetic or natural materials used for constructing artificial organs, fabricating prostheses, or replacing tissues. The last century saw the development of thousands of novel biomaterials and, as a result, an exponential increase in scientific publications in the field. Large-scale analysis of biomaterials and their performance could enable data-driven material selection and implant design. However, such analysis requires identification and organization of concepts, such as materials and structures, from published texts. To facilitate future information extraction and the application of machine-learning techniques, we developed a semantic annotator specifically tailored for the biomaterials literature. The Biomaterials Annotator has been implemented following a modular organization using software containers for the different components and orchestrated using Nextflow as workflow manager. Natural language processing (NLP) components are mainly developed in Java. This set-up has allowed named entity recognition of seventeen classes relevant to the biomaterials domain. Here we detail the development, evaluation and performance of the system, as well as the release of the first collection of annotated biomaterials abstracts. We make both the corpus and system available to the community to promote future efforts in the field and contribute towards its sustainability.
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