Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting ADR.
سم اللغة العربية بكل ما فيها من حيوية بالإبداعية في دلالاتها التي تنقلنا إلى عالم الشاعر الدلالي، ولا بدّ من أن يكون للحذف دلالاته في ضبط النغم الشّعريّ على إيقاع المعنى الذي يريد الشاعر إيصاله، فللحذف دوره في الحفاظ على تماسك النصّ الإبداعي ودوره في التعبير عما يدور في قلب الشاعر من خلجات ومعانٍ، وإذْ يعطي أسلوب الحذف مساهمة واسعة للشاعرية أن تأخذ ما تريد من ألوان التعبير بأقل عدد من الكلمات. ويعدّ سراقة الب
... Show MoreIn this work, mesoporous silica SBA-15 was prepared and functionalized with amine groups (i.e., NH2) to form NH2/SBA-15. The curcumin (CUR) was encapsulated into the surface and pore of NH2/SBA-15 to create CUR@NH2/SBA-15 as an efficient carrier in drug delivery systems (DDSs). The three samples (i.e., SBA-15, NH2/SBA-15, and CUR@NH2/SBA-15) were characterized. The study investigated the effect of the carrier dose, initial CUR concentration, pH, and contact time on the CUR loading efficiency (DLE%) via adsorption. The best DLE% for the SBA-15 and NH2/SBA-15 were found to be 45% and 89.7%, respectively. The Langmuir isotherm had a greater correlation coefficient (R2) of 0.998 for SBA-15. A pseudo-secondorder kinetic model seemed to fit well
... Show MoreThis paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining
... Show MoreThis work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the
... Show MoreThe Internet of Things (IoT) technology is every object around us and it is used to connect these objects to the Internet to verify Machine to Machine (M2M) communication. The smart house system is the most important application of IoT technology; it is increase the quality of life and decrease the efforts. There were many problems that faced the existing smart house networking systems, including the high cost of implementation and upgrading, high power consumption, and supported limited features. Therefore, this paper presents the design and implementation of smart house network system (SHNS) using Raspberry Pi and Arduino platforms as network infrastructure with ZigBee technology as wireless communication. SHNS consists of two mai
... Show MoreThe influence of the reaction gas composition during the DC magnetron sputtering process on the structural, chemical and optical properties of Ce-oxide thin films was investigated. X-ray diffraction (XRD) studies confirmed that all thin films exhibited a polycrystalline character with cubic fluorite structure for cerium dioxide. X-ray photoelectron spectroscopy (XPS) analyses revealed that cerium is present in two oxidation states, namely as CeO2 and Ce2O3, at the surface of the films prepared at oxygen/argon flow ratios between 0% and 7%, whereas the films are completely oxidized into CeO2 as the aforementioned ratio increases beyond 14%. Various optical parameters for the thin films (including an optical band gap in the range of 2.25–3.
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