文章基本信息

标题：A High Performance System for the Diagnosis of Headache via Hybrid Machine Learning Model
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作者：Ahmad Qawasmeh ; Noor Alhusan ; Feras Hanandeh 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：5
DOI：10.14569/IJACSA.2020.0110580
出版社：Science and Information Society (SAI)
摘要：Headache has been a major concern for patients, medical doctors, clinics and hospitals over the years due to several factors. Headache is categorized into two major types:(1) Primary Headache, which can be tension, cluster or migraine, and (2) Secondary Headache where further medical evaluation must be considered. This work presents a high performance Headache Prediction Support System (HPSS). HPSS provides preliminary guidance for patients, medical students and even clinicians for initial headache diagnosis. The mechanism of HPSS is based on a hybrid machine learning model. First, 19 selected attributes (questions) were chosen carefully by medical specialists according to the most recent International Classification of Headache Disorders (ICHD-3) criteria. Then, a questionnaire was prepared to confidentially collect data from real patients under the supervision of specialized clinicians at different hospitals in Jordan. Later, a hybrid solution consisting of clustering and classification was employed to emphasize the diagnosis results obtained by clinicians and to predict headache type for new patients respectively. Twenty-six (26) different classification algorithms were applied on 614 patients’ records. The highest accuracy was obtained by integrating K-Means and Random Forest with a migraine accuracy of 99.1% and an overall accuracy of 93%. Our web-based interface was developed over the hybrid model to enable patients and clinicians to use our system in the most convenient way. This work provides a comparative study of different headache diagnosis systems via 9 different performance metrics. Our hybrid model shows a great potential for highly accurate headache prediction. HPSS was used by different patients, medical students, and clinicians with a very positive feedback. This work evaluates and ranks the impact of headache symptoms on headache diagnosis from a machine learning perspective. This can help medical experts for further headache criteria improvements.
关键词：High performance computing; Clinical Decision Support System (CDSS); machine learning; primary and secondary headache; performance analysis and improvement; headache diag-nosis; open medical application