Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00027
Mohammed A Althamir, Abdullah Alabdulhay, M. M. Yasin
Symmetric and asymmetric encryption methods are used when a web browser is used to reply to emails, submit website forms, and perform similar activities. Key size is essential to enable security, which means the longer a key is, the better security can be ensured. Purpose: This review aims to present an overview of the critical size length, which is significant against different types of cyber attacks. Methodology: This research study is based on systematic literature review and secondary data analysis. Results: The symmetric and asymmetric key sizing participate in enabling data security and protection. Conclusion: Different cryptographic techniques will contribute to highlight the best approach that can be employed to maintain confidential data and address related issues within symmetric and asymmetric encryption key size.
{"title":"A Systematic Literature Review on Symmetric and Asymmetric Encryption Comparison Key Size","authors":"Mohammed A Althamir, Abdullah Alabdulhay, M. M. Yasin","doi":"10.1109/ICSMDI57622.2023.00027","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00027","url":null,"abstract":"Symmetric and asymmetric encryption methods are used when a web browser is used to reply to emails, submit website forms, and perform similar activities. Key size is essential to enable security, which means the longer a key is, the better security can be ensured. Purpose: This review aims to present an overview of the critical size length, which is significant against different types of cyber attacks. Methodology: This research study is based on systematic literature review and secondary data analysis. Results: The symmetric and asymmetric key sizing participate in enabling data security and protection. Conclusion: Different cryptographic techniques will contribute to highlight the best approach that can be employed to maintain confidential data and address related issues within symmetric and asymmetric encryption key size.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130142399","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00036
Jie Cheng, Jun Wang, Di Gao, Yaoyu Wang
Construction of scientific decision-making system for the power service integrating smart cloud platform is the main topic of this study. In recent years, the development of the power system has entered a new era, and profound changes have taken place in business requirements, technical characteristics and functional forms. Hence, the combination with the cloud system is essential. This paper considers two core functionalities: (1) the unit combination problem solution; (2) online security and stability decision of the power system guarantee as the referring targets. Through the testing under cloud scenario, the performance is then validated.
{"title":"Construction of Scientific Decision-Making System for Power Service Integrating Smart Cloud Platform","authors":"Jie Cheng, Jun Wang, Di Gao, Yaoyu Wang","doi":"10.1109/ICSMDI57622.2023.00036","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00036","url":null,"abstract":"Construction of scientific decision-making system for the power service integrating smart cloud platform is the main topic of this study. In recent years, the development of the power system has entered a new era, and profound changes have taken place in business requirements, technical characteristics and functional forms. Hence, the combination with the cloud system is essential. This paper considers two core functionalities: (1) the unit combination problem solution; (2) online security and stability decision of the power system guarantee as the referring targets. Through the testing under cloud scenario, the performance is then validated.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131541392","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00108
Juhi Chhatlani, Tejashree Mahajan, Rushabh Rijhwani, Advait Bansode, G. Bhatia
As solar energy has been recognized as an inexhaustible source of energy, the solar photovoltaic installation business has taken the lead in today's market. Nowadays, people are investing more in green energy due to its harmless and everlasting supply of energy and also its boundless applications. With the adaptation of solar panels on the building rooftops, people often fail to think of the total energy that will be generated from the solar panel and if the generated power is sufficient enough to fulfill the power requirements of the whole building. Different climate zones receive different amounts of sunlight and thus, solar energy generation varies in all regions. Artificial Intelligence has evolved to bring significant development in this field as it helps in detecting rooftops that have a potential for solar photovoltaic systems and also helps to efficiently detect how much energy can be generated using the solar panels. Latest Deep Learning models like YOLO, EfficientNet, VGG ResNet etc are able to detect rooftops using geospatial images of zones and models like U-Net, SegNet etc are used to configure the solar photovoltaic system for the consumer. An additional model for the calculation of power generated considering different parameters like climate, topography will be built using advanced AI techniques. The best performing models will be finetuned and integrated with the front end to act as a one stop destination for the end user.
{"title":"HarGharSolar : Recognition of Potential Rooftop PhotoVoltaic Arrays Using Geospatial Imagery for Diverse Climate Zones.","authors":"Juhi Chhatlani, Tejashree Mahajan, Rushabh Rijhwani, Advait Bansode, G. Bhatia","doi":"10.1109/ICSMDI57622.2023.00108","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00108","url":null,"abstract":"As solar energy has been recognized as an inexhaustible source of energy, the solar photovoltaic installation business has taken the lead in today's market. Nowadays, people are investing more in green energy due to its harmless and everlasting supply of energy and also its boundless applications. With the adaptation of solar panels on the building rooftops, people often fail to think of the total energy that will be generated from the solar panel and if the generated power is sufficient enough to fulfill the power requirements of the whole building. Different climate zones receive different amounts of sunlight and thus, solar energy generation varies in all regions. Artificial Intelligence has evolved to bring significant development in this field as it helps in detecting rooftops that have a potential for solar photovoltaic systems and also helps to efficiently detect how much energy can be generated using the solar panels. Latest Deep Learning models like YOLO, EfficientNet, VGG ResNet etc are able to detect rooftops using geospatial images of zones and models like U-Net, SegNet etc are used to configure the solar photovoltaic system for the consumer. An additional model for the calculation of power generated considering different parameters like climate, topography will be built using advanced AI techniques. The best performing models will be finetuned and integrated with the front end to act as a one stop destination for the end user.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114258795","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00029
Dandu Jeevan Sai Kumar, Shahnam Baig, Mallina Satwik Chowdary, Kondaveeti Basava Sai Manjunath, K. Prasad, Sathish Kumar Kannaiah
Big data enables the rapid generation of massive volume of data from a variety of rich data sources. Using the 2019 coronavirus disease as an example, these enormous data sets contain information on people who have had viral illnesses, as well as information on healthcare and epidemiology. (COVID19). Researchers, epidemiologists, and lawmakers can better comprehend the disease as a result of data scientists' knowledge obtained from these epidemiological data, which may inspire them to create policies for identifying, containing, and combating it. This article outlines a data science methodology for analyzing vast quantities of COVID-19 epidemiological data. This study investigates if early SARS exposure affects imprinting based on the imprinting theory. that has a significant impact fear of COVID-19 In addition, this study suggests the use of big data and AI applications will determine whether this effect occurs. The global economic, social, sociological, and health sectors were severely harmed by the COVID-19 epidemic, which also caused a sizable number of fatalities. The necessary knowledge is developed using the proper big data analytics technologies, which are then used to make judgements and take precautionary action.
{"title":"A Study on Covid-19 Analytics on Bigdata","authors":"Dandu Jeevan Sai Kumar, Shahnam Baig, Mallina Satwik Chowdary, Kondaveeti Basava Sai Manjunath, K. Prasad, Sathish Kumar Kannaiah","doi":"10.1109/ICSMDI57622.2023.00029","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00029","url":null,"abstract":"Big data enables the rapid generation of massive volume of data from a variety of rich data sources. Using the 2019 coronavirus disease as an example, these enormous data sets contain information on people who have had viral illnesses, as well as information on healthcare and epidemiology. (COVID19). Researchers, epidemiologists, and lawmakers can better comprehend the disease as a result of data scientists' knowledge obtained from these epidemiological data, which may inspire them to create policies for identifying, containing, and combating it. This article outlines a data science methodology for analyzing vast quantities of COVID-19 epidemiological data. This study investigates if early SARS exposure affects imprinting based on the imprinting theory. that has a significant impact fear of COVID-19 In addition, this study suggests the use of big data and AI applications will determine whether this effect occurs. The global economic, social, sociological, and health sectors were severely harmed by the COVID-19 epidemic, which also caused a sizable number of fatalities. The necessary knowledge is developed using the proper big data analytics technologies, which are then used to make judgements and take precautionary action.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116509747","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00010
Kuntal Gorai, S. V S C Santosh, Skanda S, Vijay Murugan A S, Prajwala Tr
Everyone has experienced waiting in long queues to get their items billed at a shopping cart. With this product, the proposed research work intends to reduce the time spent by shoppers in queues. Our automated shopping cart can reduce the time and manual labor required for weighing and billing the items a user wishes to buy. This article has developed a shopping cart with weight sensors built into the cart to measure the load of the product, and an android application with deep learning models(MobileNetV2 and EfficientNetV2) to classify the required item. The models were trained on a custom-built dataset with 51 classes. The mobile phone camera is used to capture an image of the product. The models are used to classify this item. Once the item is classified, the weight of the item is obtained from the load cells. A database analysis is performed to obtain the price of the item. With these details, the bill is generated as soon as the user is done with shopping without waiting in long queues.
{"title":"Automated Shopping Cart: Reducing Long Queues One Cart At A Time","authors":"Kuntal Gorai, S. V S C Santosh, Skanda S, Vijay Murugan A S, Prajwala Tr","doi":"10.1109/ICSMDI57622.2023.00010","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00010","url":null,"abstract":"Everyone has experienced waiting in long queues to get their items billed at a shopping cart. With this product, the proposed research work intends to reduce the time spent by shoppers in queues. Our automated shopping cart can reduce the time and manual labor required for weighing and billing the items a user wishes to buy. This article has developed a shopping cart with weight sensors built into the cart to measure the load of the product, and an android application with deep learning models(MobileNetV2 and EfficientNetV2) to classify the required item. The models were trained on a custom-built dataset with 51 classes. The mobile phone camera is used to capture an image of the product. The models are used to classify this item. Once the item is classified, the weight of the item is obtained from the load cells. A database analysis is performed to obtain the price of the item. With these details, the bill is generated as soon as the user is done with shopping without waiting in long queues.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129941260","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00094
D. Roja Ramani, Rachna P, Pavan G, R. Reddy, Mohammad Huzaifa
In today's world agriculture plays a very important role in the manufacturing of textiles, clothes, production of surplus number of crops that is food, which is essential for the everyday livelihood of mankind. On the other hand, there are a lot of challenges in the agricultural industries such as unpredictable natural disasters such as droughts, famines, floods etc., which can incur huge loss for the agriculture industries as well as the countries which have an agrarian society not only will it be affected by natural disasters but can also be affected by the diseases, which have the potential to destroy crops. The primary objective is to assist farmers and agriculture industries to thrive so that there can be less occurrence of food shortages by efficiently increasing the production of crops tenfold, analyzes the soil fertility for better plant growth, helps prevent plant epidemic by analyzing which fertilizer is better suitable for the protection of the plant to analyze the weather and the plants that is suitable to grow in the particular weather condition and predict the occurrence of natural disasters such as droughts and floods for early prevention from the crops by using the ATMEGA controller.
{"title":"Agrobot: Agricultural Robot using IoT and Machine Learning (ML)","authors":"D. Roja Ramani, Rachna P, Pavan G, R. Reddy, Mohammad Huzaifa","doi":"10.1109/ICSMDI57622.2023.00094","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00094","url":null,"abstract":"In today's world agriculture plays a very important role in the manufacturing of textiles, clothes, production of surplus number of crops that is food, which is essential for the everyday livelihood of mankind. On the other hand, there are a lot of challenges in the agricultural industries such as unpredictable natural disasters such as droughts, famines, floods etc., which can incur huge loss for the agriculture industries as well as the countries which have an agrarian society not only will it be affected by natural disasters but can also be affected by the diseases, which have the potential to destroy crops. The primary objective is to assist farmers and agriculture industries to thrive so that there can be less occurrence of food shortages by efficiently increasing the production of crops tenfold, analyzes the soil fertility for better plant growth, helps prevent plant epidemic by analyzing which fertilizer is better suitable for the protection of the plant to analyze the weather and the plants that is suitable to grow in the particular weather condition and predict the occurrence of natural disasters such as droughts and floods for early prevention from the crops by using the ATMEGA controller.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130148283","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}
Government Schemes Eligible System Research's fundamental concept is to build a technology platform to assist residents in using and determining their eligibility for online programs. Every phone in the nation will have this application loaded on it, and users may use it to see if they qualify for any programs by filling out an online application. There is a disconnection between citizens, authorities, and government initiatives while using the current system. The government has implemented several programs, but the population has not fully taken advantage of them. This issue will be resolved by the introduction of an web design that will make work easier and productive. Citizens must use the assistance of government personnel to submit their applications for the program online. Information about the application's processing will be updated. For both public and government, this technology will save time.
{"title":"Creation of Web based Eligibility System for Government Programs","authors":"Sandeep Yellisetti, Manam Anju Priya, Polavarapu Venkata Naga Rishitha Chowdary, Rangisetti Lakshmi Sravanthi","doi":"10.1109/ICSMDI57622.2023.00030","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00030","url":null,"abstract":"Government Schemes Eligible System Research's fundamental concept is to build a technology platform to assist residents in using and determining their eligibility for online programs. Every phone in the nation will have this application loaded on it, and users may use it to see if they qualify for any programs by filling out an online application. There is a disconnection between citizens, authorities, and government initiatives while using the current system. The government has implemented several programs, but the population has not fully taken advantage of them. This issue will be resolved by the introduction of an web design that will make work easier and productive. Citizens must use the assistance of government personnel to submit their applications for the program online. Information about the application's processing will be updated. For both public and government, this technology will save time.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125352763","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}
Health Care 4.0 envisions a smart and connected healthcare practices. The emerging Cyber Physical Systems (CPS) based robotic healthcare systems is the recent technological advancement that revolutionizes the healthcare industry. This study reports the innovative concepts and capabilities of the CPS-based robotic healthcare systems. The technology that empowers health care industry include, Artificial intelligence (AI), distributed computing and big data. Finally, this study discusses about the potential design and development challenges faced by CPS-based robotic healthcare systems.
{"title":"A Comprehensive Study of Robotic Healthcare System","authors":"Sanam Geethika Sai, Raparthy V.K.Sh. Akhil, V.Sasi Sushma, S.Harsha Preetham, K. Prasad, Sathish Kumar Kannaiah","doi":"10.1109/ICSMDI57622.2023.00105","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00105","url":null,"abstract":"Health Care 4.0 envisions a smart and connected healthcare practices. The emerging Cyber Physical Systems (CPS) based robotic healthcare systems is the recent technological advancement that revolutionizes the healthcare industry. This study reports the innovative concepts and capabilities of the CPS-based robotic healthcare systems. The technology that empowers health care industry include, Artificial intelligence (AI), distributed computing and big data. Finally, this study discusses about the potential design and development challenges faced by CPS-based robotic healthcare systems.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132547927","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00054
Nataasha Raul, R. Shankarmani, Padmaja Joshi
Keystroke dynamics is considered as a supporting factor of authentication. Especially in the static keystroke dynamics, the user is identified by using the timing featured, which is captured while the user enters the login ID and password. To achieve this, the user profile needs to be created with timing features. However, in a scenario like a change of password where nearly no keystroke timing data is available, non-conventional features may be helpful. This article focuses on using non-conventional features such as NumLock key, Shift key, CapsLock key, etc for identifying users during a change of password. The paper also details how to capture the non-conventional features in static keystroke dynamics and build a model that can be used in the change of nassword.
{"title":"Static Keystroke Dynamic Authentication (SKDA) Model to Authenticate User during Password Change","authors":"Nataasha Raul, R. Shankarmani, Padmaja Joshi","doi":"10.1109/ICSMDI57622.2023.00054","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00054","url":null,"abstract":"Keystroke dynamics is considered as a supporting factor of authentication. Especially in the static keystroke dynamics, the user is identified by using the timing featured, which is captured while the user enters the login ID and password. To achieve this, the user profile needs to be created with timing features. However, in a scenario like a change of password where nearly no keystroke timing data is available, non-conventional features may be helpful. This article focuses on using non-conventional features such as NumLock key, Shift key, CapsLock key, etc for identifying users during a change of password. The paper also details how to capture the non-conventional features in static keystroke dynamics and build a model that can be used in the change of nassword.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134452500","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}
Pub Date : 2023-03-01DOI: 10.1109/ICSMDI57622.2023.00053
Narinder Kumar, Sanjay Singla
Chronic Kidney Disease (CKD) is predicted by using the CKD dataset collected from different online and offline sources. Several AI techniques available to perform CKD identification use their own sources of information, such as medical images or medical information in a tabulated form with the markers collected from Electronic Health Record (HER). Researchers have designed prediction models by using publicly available standard CKD information from the University of California, Irvine's Machine Learning for enabling the validation of outcomes as well as the comparison against other models. Various systems have been designed in the previous years to perform CKD prediction based on Machine Learning (ML) and Deep Learning (DL). This study discusses about various research works that are reviewed for the CKD prediction in terms of certain parameters. This work employs ML algorithms after pre-processing the data and compares the performance to obtain the accurate result. Here, the effectiveness is computed by using F1 score, precision, accuracy, recall, and AUC score.
{"title":"Chronic Kidney Disease Prediction Techniques: A Survey","authors":"Narinder Kumar, Sanjay Singla","doi":"10.1109/ICSMDI57622.2023.00053","DOIUrl":"https://doi.org/10.1109/ICSMDI57622.2023.00053","url":null,"abstract":"Chronic Kidney Disease (CKD) is predicted by using the CKD dataset collected from different online and offline sources. Several AI techniques available to perform CKD identification use their own sources of information, such as medical images or medical information in a tabulated form with the markers collected from Electronic Health Record (HER). Researchers have designed prediction models by using publicly available standard CKD information from the University of California, Irvine's Machine Learning for enabling the validation of outcomes as well as the comparison against other models. Various systems have been designed in the previous years to perform CKD prediction based on Machine Learning (ML) and Deep Learning (DL). This study discusses about various research works that are reviewed for the CKD prediction in terms of certain parameters. This work employs ML algorithms after pre-processing the data and compares the performance to obtain the accurate result. Here, the effectiveness is computed by using F1 score, precision, accuracy, recall, and AUC score.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126321554","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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