الشبكة العصبية الاصطناعية والتحليل الدلالي الكامن لاكتشاف التفاعلات الضارة للأدوية

محتوى المقالة الرئيسي

Ahmed Adil Nafea
https://orcid.org/0000-0003-2293-1108
نازليا عمر
زهاء مبارك القفيل

الملخص

التفاعلات الدوائية الضارة (ADR) هي معلومات مهمة للتحقق من وجهة نظر المريض بشأن دواء معين. تم أخذ تعليقات ومراجعات المستخدمون المنتظمة في الاعتبار أثناء عملية جمع البيانات لاستخراج تأثيرات ال ADR عندما أبلغ المستخدم عن تأثير جانبي بعد تناول دواء معين. في الأدبيات، ركز معظم الباحثين على تقنيات التعلم الآلي لاكتشاف ADR. تعمل هذه الطرق على تدريب نموذج التصنيف باستخدام بيانات المراجعات الطبية. ومع ذلك، لا يزال هناك العديد من المشكلات الصعبة التي تواجه استخراج ال ADR، وخاصة دقة الكشف. الهدف الرئيسي من هذه الدراسة هو اقتراح الشبكات العصبية الاصطناعية (ANN) مع التحليل الدلالي الكامن (LSA) للكشف عن ال ADR. تظهر النتائج فعالية استخدام LSA مع ANN في استخراج ADR.

تفاصيل المقالة

كيفية الاقتباس
1.
الشبكة العصبية الاصطناعية والتحليل الدلالي الكامن لاكتشاف التفاعلات الضارة للأدوية. Baghdad Sci.J [انترنت]. 1 يناير، 2024 [وثق 20 مايو، 2024];21(1):0226. موجود في: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7988
القسم
article

كيفية الاقتباس

1.
الشبكة العصبية الاصطناعية والتحليل الدلالي الكامن لاكتشاف التفاعلات الضارة للأدوية. Baghdad Sci.J [انترنت]. 1 يناير، 2024 [وثق 20 مايو، 2024];21(1):0226. موجود في: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7988

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