Advanced chromatographic technique for performance simulation of anti-Alzheimer agent: an ensemble machine learning approach

Ghali, Umar Muhammad; Usman, A. G.; Chellube, Z. M.; Degm, Mohamed Alhosen Ali; Hoti, Kujtesa; Umar, Huzaifah; Abba, S.I.

doi:10.1007/s42452-020-03690-2

Cited by 28 publications

(26 citation statements)

References 28 publications

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“…In this section, the obtained results are shown both quantitatively and in a visualized form. Table 1 demonstrates the correlation analysis of the variables involved in the study (Ghali et al 2020), namely, number of abdominal writhes, number mean reaction time of paw licking and paw oedema diameter. Acetic acid-induced abdominal writhes result from the stimulation of the release of arachidonic acid to form PG that plays a critical role in pain mechanism.…”

Section: Resultsmentioning

confidence: 99%

The effect of ethanolic leaves extract of Hymenodictyon floribundun on inflammatory biomarkers: a data-driven approach

et al. 2021

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Background Medicinal plants are used to manage pain and inflammatory disorders in traditional medicine. A scientific investigation could serve as a basis for the determination of molecular mechanisms of antinociceptive and antiinflammatory actions of herbal products. In this work, we used both artificial intelligence (AI) based models inform of adaptive neuro-fuzzy inference system and artificial neural network (ANN) as well as a linear model, namely; stepwise linear regression in modelling the performance of four different inflammatory biomarkers namely; interleukin (1L)-1β, 1L-6, tumour necrosis factor (TNF)-α and prostaglandin E2 (PGE2). This modelling was done using number of abdominal writes, the reaction time of paw licking in mice and paw oedema diameter as the input variables. Results Four different performance indices were employed, which are determination coefficient (DC), root mean squared error (RMSE), mean square error (MSE) and correlation co-efficient (CC). The results have shown the superiority of the AI-based models over the linear model. Conclusions The overall quantitative and visualized comparison of the results showed that adaptive neuro-fuzzy inference system outperformed the ANN and SWLR models in modelling the performance of the four inflammation biomarkers in both the calibration and verification phases.

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Section: Resultsmentioning

confidence: 99%

The effect of ethanolic leaves extract of Hymenodictyon floribundun on inflammatory biomarkers: a data-driven approach

et al. 2021

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“…Social distancing and limitation of public and economic activities showed direct impact to the financial capability and resilience in multiple countries including studies here in Northern Cyprus. Even though many studies have stated that the using of technology, with its mobility and personalized benefits, helped lecturers promoting innovation in education, not just limited to the improvement of lecture-style teaching, but also through more humanistic approach in direct open discussion and a more controlled systematic information collection as shown in a study made in Indonesia (17). Our study results showed that out of 209 participant's shows 64.6% of participants had minimal to mild anxiety while 34.6% had moderate to severe anxiety in accordance with the generalized anxiety disorder -7 (GAD-7) scale.…”

Section: Discussionmentioning

confidence: 99%

“…Panic disorder (sensitivity 74%, specificity 81%), social anxiety disorder (sensitivity 72%, specificity 80%), and post-traumatic stress disorder (sensitivity 66%, specificity 81%) are all quite well-screened disorders. (17).…”

Section: Study Toolmentioning

confidence: 99%

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The impact of online education due to COVID-19 outbreak as a cause of anxiety among university students in Northern Cyprus using cross- sectional survey: A data driven based approach

Ibrahim¹,

Nabegu²,

Ahseen³

2021

GSC Adv. Eng. Technol.

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Introduction: Coronavirus disease (COVID-19) or severe acute respiratory syndrome is an infectious disease caused by a newly found coronavirus strain. SARS-CoV-2 coronavirus is a type of virus that causes respiratory illnesses in people. Online learning system was switched due to the COVID-19 and GAD-7 Scales were used to measure the correlation and impact of online education as a reason for anxiety among university students in Northern Cyprus. Methods: The Generalized anxiety disorder (GAD-7) scale was used to assess anxiety level. An e-questionnaire was formed using google form and shared on social media. An online survey was done, it was participated by 209 students of universities in Northern Cyprus in which the data analysis was done using statistical package for social science (SPSS), MLR, ANN, and ANFIS. Results: 209 participants 64.6% of the participants had minimal to mild anxiety and 34.6% had moderate to severe anxiety according to generalized anxiety disorder (GAD-7) scale. Almost all Students with medium economic status have minimal to mild anxiety levels. The obtained data driven approach performance results indicates the ability of the hybrid techniques over the single models in simulation of the anxiety level of the students based on the performance evaluation indices used in the current research Conclusion: The COVID-19 Outbreak imposes a serious challenge to university students undergoing online classes in Northern Cyprus as majority of the students with medium income reported to had minimal to mild anxiety which require the attention of the concern authorities to provide a solution. The proposed hybrid techniques prove to have the necessary efficiency in boosting the performance of the single models towards anxiety level of the student’s simulation.

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“…For the purpose of this research, the employed data‐driven intelligence, ANN, ANFIS, MLR models, and novel ensemble techniques, and a brief description of the mathematical concept for each of these models as well as the related citations and equations are provided in the Supporting Information Appendix (A1–A4) in more detail [28‐35].…”

Section: Methodsmentioning

confidence: 99%

Chemometrics‐based models hyphenated with ensemble machine learning for retention time simulation of isoquercitrin in Coriander sativum L. using high‐performance liquid chromatography

Usman

Işık

Abba

et al. 2021

J of Separation Science

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In this research, two nonlinear models, namely; adaptive neuro‐fuzzy inference system and feed‐forward neural network and a classical linear model were employed for the prediction of retention time of isoquercitrin in Coriander sativum L. using the high‐performance liquid chromatography technique. The prediction employed the use of composition of mobile phase and pH as the corresponding input parameters. The performance indices of the models were evaluated using root mean square error, determination co‐efficient, and correlation co‐efficient. The results obtained from the simple models showed that subclustering‐adaptive‐neuro fuzzy inference system gave the best results in both the training and testing phases and boosted the performance accuracy of the simple models. The overall comparison of the results showed that subclustering‐adaptive‐neuro fuzzy inference system ensemble demonstrated outstanding performance and increased the accuracy of the single models and ensemble models in the testing phase, up to 35% and 3%, respectively.

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Advanced chromatographic technique for performance simulation of anti-Alzheimer agent: an ensemble machine learning approach

Cited by 28 publications

References 28 publications

The effect of ethanolic leaves extract of Hymenodictyon floribundun on inflammatory biomarkers: a data-driven approach

The effect of ethanolic leaves extract of Hymenodictyon floribundun on inflammatory biomarkers: a data-driven approach

The impact of online education due to COVID-19 outbreak as a cause of anxiety among university students in Northern Cyprus using cross- sectional survey: A data driven based approach

Chemometrics‐based models hyphenated with ensemble machine learning for retention time simulation of isoquercitrin in Coriander sativum L. using high‐performance liquid chromatography

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