The largest cause of mortality worldwide is heart disease, and early identification is critical in limiting disease development. Early approaches for detecting cardiovascular illnesses assisted in determining the progressions that should have happened in high-risk persons, reducing their risks. The major goal is to save lives by recognising anomalies in cardiac circumstances, which will be performed by identifying and analysing raw data produced from cardiac information. Machine learning can provide an efficient method for making decisions and creating accurate forecasts. Machine learning techniques are being used extensively in the medical business. A unique machine learning technique is provided in the proposed study to predict cardiac disease. The planned study made advantage of open source heart disease dataset from kaggle. Hybrid algorithms for machine learning prediction are the logical mixture of many previous methodologies designed to improve efficiency and produce improved outcomes. The presented work introduces a hybrid method that employs the notion of categorization for prediction analysis. We used real patient data to build a hybrid technique to predicting cardiac disease. KNN and SVM classification techniques were utilized in this paper. Jupyter Notebook is used to implement this hybrid method. A hybrid technique outperforms other algorithms in the prediction analysis of heart disease.
{"title":"Improving Heart Disease Prediction Accuracy Using a Hybrid Machine Learning Approach: A Comparative study of SVM and KNN Algorithms","authors":"Rehan Ahmed, Maria Bibi, Sibtain Syed","doi":"10.54489/ijcim.v3i1.223","DOIUrl":"https://doi.org/10.54489/ijcim.v3i1.223","url":null,"abstract":"The largest cause of mortality worldwide is heart disease, and early identification is critical in limiting disease development. Early approaches for detecting cardiovascular illnesses assisted in determining the progressions that should have happened in high-risk persons, reducing their risks. The major goal is to save lives by recognising anomalies in cardiac circumstances, which will be performed by identifying and analysing raw data produced from cardiac information. Machine learning can provide an efficient method for making decisions and creating accurate forecasts. Machine learning techniques are being used extensively in the medical business. A unique machine learning technique is provided in the proposed study to predict cardiac disease. The planned study made advantage of open source heart disease dataset from kaggle. Hybrid algorithms for machine learning prediction are the logical mixture of many previous methodologies designed to improve efficiency and produce improved outcomes. The presented work introduces a hybrid method that employs the notion of categorization for prediction analysis. We used real patient data to build a hybrid technique to predicting cardiac disease. KNN and SVM classification techniques were utilized in this paper. Jupyter Notebook is used to implement this hybrid method. A hybrid technique outperforms other algorithms in the prediction analysis of heart disease.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116051980","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}
Federico Del Giorgio Solfa, Fernando Rogelio Simonato
Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research
{"title":"Big Data Analytics in Healthcare: Exploring the Role of Machine Learning in Predicting Patient Outcomes and Improving Healthcare Delivery","authors":"Federico Del Giorgio Solfa, Fernando Rogelio Simonato","doi":"10.54489/ijcim.v3i1.235","DOIUrl":"https://doi.org/10.54489/ijcim.v3i1.235","url":null,"abstract":"Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"66 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113957297","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}
By enabling more precise demand forecasting, the use of big data has changed the field of supply chain management. Companies may more accurately predict customer demand by gathering and analyzing enormous amounts of data from many sources, including customer behaviors and market trends, and then adjusting their production and inventory levels accordingly. By ensuring that goods and services are accessible when and where they are required, this improves customer happiness in addition to the efficiency and cost-effectiveness of the supply chain. The data collected from both primary and secondary sources to achieve the research objectives. The data collected from hospitality industry and evaluated through SmartPLS software to investigate the hypothesized model. An online survey through a questionnaire was the data collection tools used for attaining data. A survey analysis was conducted on the individuals employed to the supply chain departments. In addition, the findings revealed a positive significant of big data on supply chain performance through demand forecasting. Overall, the impact of big data on supply chain performance through demand forecasting is significant and continues to drive innovation and improvement in the hospitality sector.
{"title":"Impact of Big Data on Supply Chain Performance through Demand Forecasting","authors":"Pastor Arguelles JR., Z. Pólkowski","doi":"10.54489/ijcim.v3i1.232","DOIUrl":"https://doi.org/10.54489/ijcim.v3i1.232","url":null,"abstract":"By enabling more precise demand forecasting, the use of big data has changed the field of supply chain management. Companies may more accurately predict customer demand by gathering and analyzing enormous amounts of data from many sources, including customer behaviors and market trends, and then adjusting their production and inventory levels accordingly. By ensuring that goods and services are accessible when and where they are required, this improves customer happiness in addition to the efficiency and cost-effectiveness of the supply chain. The data collected from both primary and secondary sources to achieve the research objectives. The data collected from hospitality industry and evaluated through SmartPLS software to investigate the hypothesized model. An online survey through a questionnaire was the data collection tools used for attaining data. A survey analysis was conducted on the individuals employed to the supply chain departments. In addition, the findings revealed a positive significant of big data on supply chain performance through demand forecasting. Overall, the impact of big data on supply chain performance through demand forecasting is significant and continues to drive innovation and improvement in the hospitality sector.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114446532","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}
Muthmainnah, Ahmad Al Yakin, Prodhan Mahbub Ibna Seraj
Metaverse technology, encompassing virtual reality (VR) and augmented reality (AR), offers immersive and interactive learning environments that can enhance student engagement. The personalized and adaptive nature of metaverse experiences has the potential to spark students' intrinsic motivation and promote active involvement in their learning. In order to evaluate the impact of metaverse technology on academic performance and level of engagement this research was aimed to assess the academic performance with mediating effect of learning motivation. We conducted an empirical research through an online survey that initially utilized to measure the collected data. Data collected from 33 educational institution located in Dubai UAE. A total of 251 respondent’s data were utilized and assessed through structured equation modelling. SmartPLS 4 was used to check the model convergent validity, discriminant validity and hypothesis testing. The findings revealed student involvement can be positively impacted by the employment of metaverse technology, which in turn improves academic performance. However, it's critical to take into account potential access restrictions and the necessity for a well-rounded educational strategy that combines metaverse experiences with other teaching strategies. Future studies should focus on the precise mechanisms by which metaverse technology influences learning motivation, engagement, and performance, as this will give researchers important information for developing efficient metaverse-based educational interventions.
{"title":"Impact of Metaverse Technology on Student Engagement and Academic Performance: The Mediating Role of Learning Motivation","authors":"Muthmainnah, Ahmad Al Yakin, Prodhan Mahbub Ibna Seraj","doi":"10.54489/ijcim.v3i1.234","DOIUrl":"https://doi.org/10.54489/ijcim.v3i1.234","url":null,"abstract":"Metaverse technology, encompassing virtual reality (VR) and augmented reality (AR), offers immersive and interactive learning environments that can enhance student engagement. The personalized and adaptive nature of metaverse experiences has the potential to spark students' intrinsic motivation and promote active involvement in their learning. In order to evaluate the impact of metaverse technology on academic performance and level of engagement this research was aimed to assess the academic performance with mediating effect of learning motivation. We conducted an empirical research through an online survey that initially utilized to measure the collected data. Data collected from 33 educational institution located in Dubai UAE. A total of 251 respondent’s data were utilized and assessed through structured equation modelling. SmartPLS 4 was used to check the model convergent validity, discriminant validity and hypothesis testing. The findings revealed student involvement can be positively impacted by the employment of metaverse technology, which in turn improves academic performance. However, it's critical to take into account potential access restrictions and the necessity for a well-rounded educational strategy that combines metaverse experiences with other teaching strategies. Future studies should focus on the precise mechanisms by which metaverse technology influences learning motivation, engagement, and performance, as this will give researchers important information for developing efficient metaverse-based educational interventions.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116174062","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}
Online operations are becoming a crucial component of the healthcare ecosystem in the modern world. But, as technology has become more widely used, so too has the risk of cyberattacks grown. Implementing information security measures is therefore crucial if we are to preserve sensitive patient data and maintain online operations. By recognizing, evaluating, and controlling possible dangers, risk management is essential in reducing these risks. In order to understand how information security affects online operations in the healthcare sector, this study will look at the mediating role of risk management. A hypothetical model was assessed using SmartPLS 4.0 containing 132 respondent’s data from 56 healthcare providers (hospitals) in Dubai UAE. The empirical results can offer insightful information about the significance of information security and risk management in guaranteeing the security and safety of sensitive patient data in the context of online healthcare.
{"title":"Impact of Information Security on Online Operations: The Mediating Role of Risk Management","authors":"Keltoum Bentameur, Boudjema Iguenane","doi":"10.54489/ijcim.v3i1.224","DOIUrl":"https://doi.org/10.54489/ijcim.v3i1.224","url":null,"abstract":"Online operations are becoming a crucial component of the healthcare ecosystem in the modern world. But, as technology has become more widely used, so too has the risk of cyberattacks grown. Implementing information security measures is therefore crucial if we are to preserve sensitive patient data and maintain online operations. By recognizing, evaluating, and controlling possible dangers, risk management is essential in reducing these risks. In order to understand how information security affects online operations in the healthcare sector, this study will look at the mediating role of risk management. A hypothetical model was assessed using SmartPLS 4.0 containing 132 respondent’s data from 56 healthcare providers (hospitals) in Dubai UAE. The empirical results can offer insightful information about the significance of information security and risk management in guaranteeing the security and safety of sensitive patient data in the context of online healthcare.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115710682","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}
The research focuses on the potential for customers of different goods and services to adopt an Internet-based buying attitude that is more intensive than the current scenario inside the UAE. The access of Internet, the volume of Internet usage, and consumer knowledge of e-commerce are used to assess customers' e-readiness. Taken into account in the research a total of 264 e-transactions permitted clients from the cities were included in the study. Three different analyses and multiple regression analysis have been employed to determine out that the original desire of the residents of Dubai and Sharjah. Our examination used a descriptive methodology and survey technique to address relevant results and their implications for probable B2C e-shopping adoption in the nation's shopping activities.
{"title":"Technology Acceptance Model and Attitude of Consumers towards Online Shopping with Special Reference to UAE","authors":"H. Purohit, Deepak Kalra, H. K. Nair","doi":"10.54489/ijcim.v3i1.233","DOIUrl":"https://doi.org/10.54489/ijcim.v3i1.233","url":null,"abstract":"The research focuses on the potential for customers of different goods and services to adopt an Internet-based buying attitude that is more intensive than the current scenario inside the UAE. The access of Internet, the volume of Internet usage, and consumer knowledge of e-commerce are used to assess customers' e-readiness. Taken into account in the research a total of 264 e-transactions permitted clients from the cities were included in the study. Three different analyses and multiple regression analysis have been employed to determine out that the original desire of the residents of Dubai and Sharjah. Our examination used a descriptive methodology and survey technique to address relevant results and their implications for probable B2C e-shopping adoption in the nation's shopping activities.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114421060","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}
For every sector, managing supply chains is a difficult task, but the healthcare sector faces risks and complication since a disrupted supply chain could have a direct impact on patient security and medical results. In this assignment we will discuss how Blockchain technology is one possible method for enhancing the health E-supply chain's security, integrity, data provenance, and usefulness. The medical supply, medical product and supply, Internet of Medical Things (IOMT), and health care sector are all given such priority, the goal of this research is to provide a description of the advantages and drawbacks of using blockchain technology in the medical distribution and supply network. The unfulfilled potential of blockchain technology to increase the health supply chain requires greater research, analysis, and integration with regulatory frameworks has been discussed.
{"title":"A SYSTEMATIC REVIEW OF BLOCKCHAIN TECHNOLOGY USE IN E-SUPPLY CHAIN IN INTERNET OF MEDICAL THINGS (IOMT)","authors":"Romil Rawat","doi":"10.54489/ijcim.v2i2.119","DOIUrl":"https://doi.org/10.54489/ijcim.v2i2.119","url":null,"abstract":"For every sector, managing supply chains is a difficult task, but the healthcare sector faces risks and complication since a disrupted supply chain could have a direct impact on patient security and medical results. In this assignment we will discuss how Blockchain technology is one possible method for enhancing the health E-supply chain's security, integrity, data provenance, and usefulness. The medical supply, medical product and supply, Internet of Medical Things (IOMT), and health care sector are all given such priority, the goal of this research is to provide a description of the advantages and drawbacks of using blockchain technology in the medical distribution and supply network. The unfulfilled potential of blockchain technology to increase the health supply chain requires greater research, analysis, and integration with regulatory frameworks has been discussed.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122771131","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}
A technology answer to the world's health concerns, ubiquitous healthcare is being considered. A combination of rising healthcare expenses and a growing demand for high-quality medical care has led to this. The development of the Internet of Things (IoT) has a greater impact on IoMT. Improved health care and safety are being provided to millions of people worldwide as a result of the Internet of Things (IoMT). Remote monitoring and transfer of data can provide medical data centres, such as those in the cloud, with real-time access to patient health characteristics. As a result, healthcare is more accessible, more effective, and less expensive. It's a problem, however, because of the proliferation of Internet of Things devices. This poses a problem because IoMT devices are compact and have a limited number of schemes and computing power. It is challenging to administer and safeguard IoMT systems because of their widespread use. This is a major problem that prevents the therapeutic application of IoMT. Internet of Things (IoT) security issues, threats, requirements, and potential future research are all covered in this report. Existing solutions and unresolved issues in the realms of security and privacy are also receiving considerable attention. This paper provides a general overview of the various art techniques by using a recognised solution.
{"title":"A LITERATURE SURVEY OF SECURITY AND PRIVACY ISSUES IN INTERNET OF MEDICAL THINGS","authors":"Jesús C. Téllez Gaytán","doi":"10.54489/ijcim.v2i2.106","DOIUrl":"https://doi.org/10.54489/ijcim.v2i2.106","url":null,"abstract":"A technology answer to the world's health concerns, ubiquitous healthcare is being considered. A combination of rising healthcare expenses and a growing demand for high-quality medical care has led to this. The development of the Internet of Things (IoT) has a greater impact on IoMT. Improved health care and safety are being provided to millions of people worldwide as a result of the Internet of Things (IoMT). Remote monitoring and transfer of data can provide medical data centres, such as those in the cloud, with real-time access to patient health characteristics. As a result, healthcare is more accessible, more effective, and less expensive. It's a problem, however, because of the proliferation of Internet of Things devices. This poses a problem because IoMT devices are compact and have a limited number of schemes and computing power. It is challenging to administer and safeguard IoMT systems because of their widespread use. This is a major problem that prevents the therapeutic application of IoMT. Internet of Things (IoT) security issues, threats, requirements, and potential future research are all covered in this report. Existing solutions and unresolved issues in the realms of security and privacy are also receiving considerable attention. This paper provides a general overview of the various art techniques by using a recognised solution.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127690874","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}
The Internet of Medical Things (IoMT) is, in fact, a fast-developing healthcare technology that has a great deal of room for improvement in terms of security. Like any other device that is linked to the internet, IoMT is susceptible to security flaws. These breaches have the potential to have an influence not just on the operation of the device, but also on the security and privacy of the data (S&P). The fallout from these violations may have potentially catastrophic and even life-threatening effects. A stakeholder-centric approach was used in the technique that was developed, with the goal of increasing the level of security of transportable IoMT devices. The suggested technique to measure the level of security present inside wearable IoMT’s is based on a combination of S&P characteristics that have been defined for such devices. Second, a technique was developed for measuring the level of security included inside such devices. At the end of the presentation, a case study was given to show how the conceptual framework may be used to the grading of Wearable IoMT’s with regard to features of S&P. The purpose of this paper is to assist hesitant consumers in choosing an IoMT device that is secure, to encourage healthy competition among makers of IoMT devices, and to ultimately raise the bar for the safety of mobile IoMT devices
{"title":"STAKEHOLDERS' PERSPECTIVES ON WEARABLE INTERNET OF MEDICAL THINGS PRIVACY AND SECURITY","authors":"Najla Sraidi","doi":"10.54489/ijcim.v2i2.109","DOIUrl":"https://doi.org/10.54489/ijcim.v2i2.109","url":null,"abstract":"The Internet of Medical Things (IoMT) is, in fact, a fast-developing healthcare technology that has a great deal of room for improvement in terms of security. Like any other device that is linked to the internet, IoMT is susceptible to security flaws. These breaches have the potential to have an influence not just on the operation of the device, but also on the security and privacy of the data (S&P). The fallout from these violations may have potentially catastrophic and even life-threatening effects. A stakeholder-centric approach was used in the technique that was developed, with the goal of increasing the level of security of transportable IoMT devices. The suggested technique to measure the level of security present inside wearable IoMT’s is based on a combination of S&P characteristics that have been defined for such devices. Second, a technique was developed for measuring the level of security included inside such devices. At the end of the presentation, a case study was given to show how the conceptual framework may be used to the grading of Wearable IoMT’s with regard to features of S&P. The purpose of this paper is to assist hesitant consumers in choosing an IoMT device that is secure, to encourage healthy competition among makers of IoMT devices, and to ultimately raise the bar for the safety of mobile IoMT devices","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124228804","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}
Numerous opportunities are emerging due to the Internet of Things' (IoT) rapid development, which has the potential to significantly improve human quality of life in many areas. The healthcare industry is the main place where IoT can enhance our quality of lives. Security and privacy concerns, however, take center stage in electronic health (eHealth) systems, and the incorporation of IoT makes them increasingly difficult to address. Due to the numerous stakeholders in its broader ecosystem, the majority of IoMT which raises security concerns. The IoT-based healthcare system has various security features. This search provides an Identity-Based Cryptography cornerstone management technique that uses collaborative authentication and a secret passcode to protect transformation of data between any IoT health device and any other entity from a different company or domain (IBC).
{"title":"INVESTIGATING THE IMPORTANCE OF ETHICS AND SECURITY ON INTERNET OF MEDICAL THINGS (IoMT)","authors":"Asaad Ali Karam","doi":"10.54489/ijcim.v2i2.114","DOIUrl":"https://doi.org/10.54489/ijcim.v2i2.114","url":null,"abstract":"Numerous opportunities are emerging due to the Internet of Things' (IoT) rapid development, which has the potential to significantly improve human quality of life in many areas. The healthcare industry is the main place where IoT can enhance our quality of lives. Security and privacy concerns, however, take center stage in electronic health (eHealth) systems, and the incorporation of IoT makes them increasingly difficult to address. Due to the numerous stakeholders in its broader ecosystem, the majority of IoMT which raises security concerns. The IoT-based healthcare system has various security features. This search provides an Identity-Based Cryptography cornerstone management technique that uses collaborative authentication and a secret passcode to protect transformation of data between any IoT health device and any other entity from a different company or domain (IBC).","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115756652","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：