Farouq Ahmad Faleh Alazzam, Hisham Jadallah Mansour Shakhatreh, Zaid Ibrahim Yousef Gharaibeh, Iryna Didiuk, Oleksandr Sylkin
{"title":"Developing an Information Model for E-Commerce Platforms: A Study on Modern Socio-Economic Systems in the Context of Global Digitalization and Legal Compliance","authors":"Farouq Ahmad Faleh Alazzam, Hisham Jadallah Mansour Shakhatreh, Zaid Ibrahim Yousef Gharaibeh, Iryna Didiuk, Oleksandr Sylkin","doi":"10.18280/isi.280417","DOIUrl":"https://doi.org/10.18280/isi.280417","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135988967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we present a machine learning-based approach for the detection of glucose levels in type 2 diabetes patients. Our approach utilizes physiological parameters such as Body Mass Index (BMI), age, sex, and blood pressure, along with glucose levels, to train a predictive model. A dataset comprising demographic information, clinical history, and laboratory test results of 500 type 2 diabetes patients was collected for training and validation. Logistic regression, support vector machines, and random forest classifiers were trained and evaluated using various performance metrics, including accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic (ROC) curve. Results showed that the random forest classifier outperformed the other models, achieving an accuracy of 85% and an AUC-ROC score of 0.90. Feature importance analysis identified age, BMI, and blood pressure as the most critical predictors for glucose level detection in type 2 diabetes patients. Our proposed machine learning-based approach demonstrates promising results for the accurate detection of glucose levels in type 2 diabetes patients. It has the potential to assist healthcare professionals in making timely and accurate decisions regarding diabetes management. Furthermore, our findings provide valuable insights into the essential predictors for glucose level detection, which can guide future research in this area.
{"title":"Feature Importance Analysis for Glucose Level Detection in Type 2 Diabetes using Machine Learning","authors":"Bollu Manikyala Rao, Mohammed Ali Hussain","doi":"10.18280/isi.280407","DOIUrl":"https://doi.org/10.18280/isi.280407","url":null,"abstract":"In this paper, we present a machine learning-based approach for the detection of glucose levels in type 2 diabetes patients. Our approach utilizes physiological parameters such as Body Mass Index (BMI), age, sex, and blood pressure, along with glucose levels, to train a predictive model. A dataset comprising demographic information, clinical history, and laboratory test results of 500 type 2 diabetes patients was collected for training and validation. Logistic regression, support vector machines, and random forest classifiers were trained and evaluated using various performance metrics, including accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic (ROC) curve. Results showed that the random forest classifier outperformed the other models, achieving an accuracy of 85% and an AUC-ROC score of 0.90. Feature importance analysis identified age, BMI, and blood pressure as the most critical predictors for glucose level detection in type 2 diabetes patients. Our proposed machine learning-based approach demonstrates promising results for the accurate detection of glucose levels in type 2 diabetes patients. It has the potential to assist healthcare professionals in making timely and accurate decisions regarding diabetes management. Furthermore, our findings provide valuable insights into the essential predictors for glucose level detection, which can guide future research in this area.","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136036828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nagireddy Venkata Raja Sekhar Reddy, Chengamma Chitteti, Sreeraman Yesupadam, Venkata Subbaiah Desanamukula, Sai Srinivas Vellela, Naga Jagadesh Bommagani
{"title":"Enhanced Speckle Noise Reduction in Breast Cancer Ultrasound Imagery Using a Hybrid Deep Learning Model","authors":"Nagireddy Venkata Raja Sekhar Reddy, Chengamma Chitteti, Sreeraman Yesupadam, Venkata Subbaiah Desanamukula, Sai Srinivas Vellela, Naga Jagadesh Bommagani","doi":"10.18280/isi.280426","DOIUrl":"https://doi.org/10.18280/isi.280426","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135988917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hybrid Deep Learning Approach and Word2Vec Feature Expansion for Cyberbullying Detection on Indonesian Twitter","authors":"Irfan Ahmad Asqolani, Erwin Budi Setiawan","doi":"10.18280/isi.280410","DOIUrl":"https://doi.org/10.18280/isi.280410","url":null,"abstract":"ABSTRACT","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135989002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Naive Bayes-Driven Mechanism for Mitigating Packet-Dropping Attacks in Autonomous Wireless Networks","authors":"Desai Neela Megha Shyam, Mohammed Ali Hussain","doi":"10.18280/isi.280422","DOIUrl":"https://doi.org/10.18280/isi.280422","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"382 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135990513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhanced Spine Segmentation in Scoliosis X-ray Images via U-Net","authors":"Sissy Sacharisa, Iman Herwidiana Kartowisastro","doi":"10.18280/isi.280427","DOIUrl":"https://doi.org/10.18280/isi.280427","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135988637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Utilizing Deep Learning and SVM Models for Schizophrenia Detection and Symptom Severity Estimation Through Structural MRI","authors":"Sheriff Alimi, Afolashade Oluwakemi Kuyoro, Monday Okpoto Eze, Oyebola Akande","doi":"10.18280/isi.280419","DOIUrl":"https://doi.org/10.18280/isi.280419","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135988690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing Indoor Navigation Accuracy with a Smartphone-Based Pedometer System","authors":"Aeshah Tareq Abdulateef, Saad A. Makki","doi":"10.18280/isi.280412","DOIUrl":"https://doi.org/10.18280/isi.280412","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135988108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring the Catalysts and Components of Gamification in Enterprise: A Systematic Literature Review","authors":"Rawaa Khalid AlTuraif, Duha Sami AlSanad, Nour Faisal AlSharifi, Amnah Abdulateef Almuaili","doi":"10.18280/isi.280418","DOIUrl":"https://doi.org/10.18280/isi.280418","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135988323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Autonomous Multi-Agent System for Customized Scientific Literature Recommendation: A Tool for Researchers and Students","authors":"Berraouna Abdelkader","doi":"10.18280/isi.280401","DOIUrl":"https://doi.org/10.18280/isi.280401","url":null,"abstract":"","PeriodicalId":38604,"journal":{"name":"Ingenierie des Systemes d''Information","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135782569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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