International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management最新文献_第2页

Logistic random forest boosting technique for Alzheimer's diagnosis. Logistic随机森林增强技术在阿尔茨海默病诊断中的应用。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-023-01187-w

K Aditya Shastry, Sheik Abdul Sattar

{"title":"Logistic random forest boosting technique for Alzheimer's diagnosis.","authors":"K Aditya Shastry, Sheik Abdul Sattar","doi":"10.1007/s41870-023-01187-w","DOIUrl":"https://doi.org/10.1007/s41870-023-01187-w","url":null,"abstract":"Alzheimer's disease (AD) is a common and well-known neurodegenerative condition that causes cognitive impairment. In the field of medicine, it is the \"nervous system\" disorder that has received the most attention. Despite this extensive research, there is no treatment or strategy to slow or stop its spread. Nevertheless, there are a variety of options (medication and non-medication alternatives) that may aid in the treatment of AD symptoms at their various phases, thereby enhancing the patient's quality of life. As AD advances over time, it is necessary to treat patients at their various stages appropriately. As a result, detecting and classifying AD phases prior to symptom treatment can be beneficial. Approximately twenty years ago, the rate of progress in the field of machine learning (ML) accelerated dramatically. Using ML methods, this study focuses on early AD identification. The \"Alzheimer's Disease Neuroimaging Initiative\" (ADNI) dataset was subjected to exhaustive testing for AD identification. The purpose was to classify the dataset into three groups: AD, \"Cognitive Normal\" (CN), and \"Late Mild Cognitive Impairment\" (LMCI). In this paper, we present the ensemble model Logistic Random Forest Boosting (LRFB), representing the ensemble of \"Logistic Regression\" (LR), \"Random Forest\" (RF), and \"Gradient Boost\" (GB). The proposed LRFB outperformed LR, RF, GB, \"k-Nearest Neighbour\" (k-NN), \"Multi-Layer Perceptron\" (MLP), \"Support Vector Machine\" (SVM), \"AdaBoost\" (AB), \"Naïve Bayes\" (NB), \"XGBoost\" (XGB), \"Decision Tree\" (DT), and other ensemble ML models with respect to the performance metrics \"Accuracy\" (Acc), \"Recall\" (Rec), \"Precision\" (Prec), and \"F1-Score\" (FS).","PeriodicalId":73455,"journal":{"name":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983513/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9305474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Editorial. 社论。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-023-01156-3

M N Hoda

引用次数: 0

A framework for vehicle quality evaluation based on interpretable machine learning. 基于可解释机器学习的车辆质量评价框架。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-022-01121-6

Mohammad Alwadi, Girija Chetty, Mohammad Yamin

引用次数: 6

COVID-19 assessment using HMM cough recognition system. 基于HMM咳嗽识别系统的COVID-19评估。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-022-01120-7

Mohamed Hamidi, Ouissam Zealouk, Hassan Satori, Naouar Laaidi, Amine Salek

引用次数: 9

Predicting opinion evolution based on information diffusion in social networks using a hybrid fuzzy based approach. 基于信息扩散的混合模糊预测社会网络中的意见演变。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-022-01109-2

Samson Ebenezar Uthirapathy, Domnic Sandanam

{"title":"Predicting opinion evolution based on information diffusion in social networks using a hybrid fuzzy based approach.","authors":"Samson Ebenezar Uthirapathy, Domnic Sandanam","doi":"10.1007/s41870-022-01109-2","DOIUrl":"https://doi.org/10.1007/s41870-022-01109-2","url":null,"abstract":"Social media plays an important role in disseminating information and analysing public and government opinions. The vast majority of previous research has examined information diffusion and opinion analysis separately. This study proposes a new framework for analysing both information diffusion and opinion evolution. The change in opinion over time is known as opinion evolution. To propose a new model for predicting information diffusion and opinion analysis in social media, a forest fire algorithm, cuckoo search, and fuzzy c-means clustering are used. The forest fire algorithm is used to determine the diffuser and non-diffuser of information in social networks, and fuzzy c-means clustering with the cuckoo search optimization algorithm is proposed to cluster Twitter content into various opinion categories and to determine opinion change. On different Twitter data sets, the proposed model outperformed the existing methods in terms of precision, recall, and accuracy.","PeriodicalId":73455,"journal":{"name":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9209471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The moderating role of trust in government adoption e-service during Covid-19 pandemic: health belief model perspective. Covid-19大流行期间信任对政府采用电子服务的调节作用:健康信念模型视角

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-023-01203-z

Dony Martinus Sihotang, Muhammad Raihan Andriqa, Futuh Nurmuntaha Alfahmi, Abdurrohim Syahruromadhon Wahyudi, Muhammad Alif Herdin Besila, Muhamad Agung Yulianang, Etti Diana, Achmad Nizar Hidayanto

{"title":"The moderating role of trust in government adoption e-service during Covid-19 pandemic: health belief model perspective.","authors":"Dony Martinus Sihotang, Muhammad Raihan Andriqa, Futuh Nurmuntaha Alfahmi, Abdurrohim Syahruromadhon Wahyudi, Muhammad Alif Herdin Besila, Muhamad Agung Yulianang, Etti Diana, Achmad Nizar Hidayanto","doi":"10.1007/s41870-023-01203-z","DOIUrl":"https://doi.org/10.1007/s41870-023-01203-z","url":null,"abstract":"The present paper discusses the influence of factors in the health belief model (HBM) on adopting government e-services during the Covid-19 pandemic in Indonesia. Furthermore, the present study demonstrates the moderating effect of trust in HBM. Therefore, we propose an interacting model between trust and HBM. A survey of 299 citizens in Indonesia was used to test the proposed model. By using a structural equation model (SEM), this study found that the HBM factors (perceived susceptibility, perceived benefit, perceived barriers, self-efficacy, cues to action, health concern) significantly affect the intention to adopt government e-services during the Covid-19 pandemic, except for the perceived severity factor. In addition, this study reveals the role of the trust variable, which significantly strengthens the effect of HBM on government e-service.","PeriodicalId":73455,"journal":{"name":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990007/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9305471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Extracting information and inferences from a large text corpus. 从大型文本语料库中提取信息和推论。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-022-01123-4

Sandhya Avasthi, Ritu Chauhan, Debi Prasanna Acharjya

{"title":"Extracting information and inferences from a large text corpus.","authors":"Sandhya Avasthi, Ritu Chauhan, Debi Prasanna Acharjya","doi":"10.1007/s41870-022-01123-4","DOIUrl":"https://doi.org/10.1007/s41870-022-01123-4","url":null,"abstract":"The usage of various software applications has grown tremendously due to the onset of Industry 4.0, giving rise to the accumulation of all forms of data. The scientific, biological, and social media text collections demand efficient machine learning methods for data interpretability, which organizations need in decision-making of all sorts. The topic models can be applied in text mining of biomedical articles, scientific articles, Twitter data, and blog posts. This paper analyzes and provides a comparison of the performance of Latent Dirichlet Allocation (LDA), Dynamic Topic Model (DTM), and Embedded Topic Model (ETM) techniques. An incremental topic model with word embedding (ITMWE) is proposed that processes large text data in an incremental environment and extracts latent topics that best describe the document collections. Experiments in both offline and online settings on large real-world document collections such as CORD-19, NIPS papers, and Tweet datasets show that, while LDA and DTM is a good model for discovering word-level topics, ITMWE discovers better document-level topic groups more efficiently in a dynamic environment, which is crucial in text mining applications.","PeriodicalId":73455,"journal":{"name":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10648535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A two-staged NLP-based framework for assessing the sentiments on Indian supreme court judgments. 一个基于NLP的两阶段框架，用于评估对印度最高法院判决的情绪。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 Epub Date: 2023-04-27 DOI: 10.1007/s41870-023-01273-z

Isha Gupta, Indranath Chatterjee, Neha Gupta

引用次数: 1

Editorial. 社论。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-023-01293-9

M N Hoda

引用次数: 0

Data analytics and knowledge management approach for COVID-19 prediction and control. COVID-19预测和控制的数据分析和知识管理方法。

International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management Pub Date : 2023-01-01 DOI: 10.1007/s41870-022-00967-0

Iqbal Hasan, Prince Dhawan, S A M Rizvi, Sanjay Dhir

{"title":"Data analytics and knowledge management approach for COVID-19 prediction and control.","authors":"Iqbal Hasan, Prince Dhawan, S A M Rizvi, Sanjay Dhir","doi":"10.1007/s41870-022-00967-0","DOIUrl":"https://doi.org/10.1007/s41870-022-00967-0","url":null,"abstract":"The Coronavirus Disease (COVID-19) caused by SARS-CoV-2, continues to be a global threat. The major global concern among scientists and researchers is to develop innovative digital solutions for prediction and control of infection and to discover drugs for its cure. In this paper we developed a strategic technical solution for surveillance and control of COVID-19 in Delhi-National Capital Region (NCR). This work aims to elucidate the Delhi COVID-19 Data Management Framework, the backend mechanism of integrated Command and Control Center (iCCC) with plugged-in modules for various administrative, medical and field operations. Based on the time-series data extracted from iCCC repository, the forecasting of COVID-19 spread has been carried out for Delhi using the Auto-Regressive Integrated Moving Average (ARIMA) model as it can effectively predict the logistics requirements, active cases, positive patients, and death rate. The intelligence generated through this research has paved the way for the Government of National Capital Territory Delhi to strategize COVID-19 related policies formulation and implementation on real time basis. The outcome of this innovative work has led to the drastic reduction in COVID-19 positive cases and deaths in Delhi-NCR.","PeriodicalId":73455,"journal":{"name":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188422/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10829533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25