Template based medical reports summarization : ministry of health case study

العناوين الأخرى

تلخيص التقارير الطبية معتمدة على قوالب وزارة الصحة : دراسة حالة

مقدم أطروحة جامعية

Abu al-Qumsan, Ahmad Yunus Muhammad

مشرف أطروحة جامعية

al-Hulays, Ala Mustafa

الجامعة

الجامعة الإسلامية

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

تكنولوجيا المعلومات

دولة الجامعة

فلسطين (قطاع غزة)

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2017

الملخص الإنجليزي

The torrential information in the medical records is considered a great problem because it is difficult to distinguish the needed and necessary information from the huge quantity of data.

As a result, the importance of summarize medical reports is growing day after day.

Medical information extraction is one of the important topic that aims to identify medical information and detect hidden relations.

This topic is considered one of the most important topics in the field of text mining where is used to process unstructured texts and extract meaningful information which is hidden in the unstructured texts.

The information extracted from medical reports is very useful to medical staff to detect hidden relations between medical information, and making decisions that will improve the medical service for patients, in addition to saving time and effort.

In our research, we propose to develop an approach that use template based medical reports summarization to transfer medical reports from semi structured and unstructured form to structured form.

It classifies the identified entities then extracts important information such as diseases, medical procedures, and drugs.

After that, we can discovery hidden relationship between medical information by using association rules.

The dataset we used in this research was collected from the Palestinian Ministry of Health.

To evaluate the performance and effectiveness of our extracted association rules, we used human experts as a reference to measure the degree of acceptance of the extracted association rules which have been extracted from the dataset to assess the accuracy of information extracted from medical reports.

So, we used Likert’s scale for evaluation.

After the data analysis obtained from the questionnaire.

It shows us that the proportion of accuracy association rules, which have been extracted is about 80%.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

عدد الصفحات

92

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-905269