Pub Date : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673250
B. P. Lohani, M. Thirunavukkarasan
After Covid 19 Pandemic people are more focusing on healthcare. Every person wants to get the solution related to any health issue from their doorstep, this is the reason that Machine learning techniques has been adopted very fast in the field of medical diagnosis which can provide fast and accurate diagnosis results at the time of disease diagnosis step this system will assist physician to predict the diseases in early stage. Using Machine learning the correct diagnosis can be done when the system will get the complete, sufficient and proper information with respect to the problem. Because of if the system will not get the proper information related to the disease this will leads to some diagnostic error by this adverse impact on the treatment of the patient. Machine learning works upon the concept of train and test the machine with the required algorithm which can provide efficient result for execution of this process first we need to train the machine with respect to the data collected and after collecting the data, data cleaning processing to be done efficiently so that we get the correct feature extraction when we follow the test step. In this research paper we are presenting comparative analysis of various machine learning algorithm ie. Linear regression. Decision tree, SVM, Random Forest etc. Applied in the field of medical diagnosis our analysis in focusing on the criteria with respect to the accuracy, performance and algorithm is applied for medical diagnosis.
{"title":"A Review: Application of Machine Learning Algorithm in Medical Diagnosis","authors":"B. P. Lohani, M. Thirunavukkarasan","doi":"10.1109/ICTAI53825.2021.9673250","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673250","url":null,"abstract":"After Covid 19 Pandemic people are more focusing on healthcare. Every person wants to get the solution related to any health issue from their doorstep, this is the reason that Machine learning techniques has been adopted very fast in the field of medical diagnosis which can provide fast and accurate diagnosis results at the time of disease diagnosis step this system will assist physician to predict the diseases in early stage. Using Machine learning the correct diagnosis can be done when the system will get the complete, sufficient and proper information with respect to the problem. Because of if the system will not get the proper information related to the disease this will leads to some diagnostic error by this adverse impact on the treatment of the patient. Machine learning works upon the concept of train and test the machine with the required algorithm which can provide efficient result for execution of this process first we need to train the machine with respect to the data collected and after collecting the data, data cleaning processing to be done efficiently so that we get the correct feature extraction when we follow the test step. In this research paper we are presenting comparative analysis of various machine learning algorithm ie. Linear regression. Decision tree, SVM, Random Forest etc. Applied in the field of medical diagnosis our analysis in focusing on the criteria with respect to the accuracy, performance and algorithm is applied for medical diagnosis.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131136215","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 study aims to predict the chronic disease of different patients using a multilayer convolution deep learning approach, which is a method of deep learning model that treats the input medical data as a vector representation. Additionally, the benefit of multi-layer perceptron is a class of neural networks in a feed-forward way which comprises mainly three layers of processing nodes for the detection of chronic diseases. The proposed system performed an efficient prediction for the diseases based on the mechanism which detects the patient can have a high rate of chronic conditions based on chronic illness. The proposed system accurately predicted that the patients are having a high rate of depressions, fatigue, joint pains, heart diseases, and strokes as chronic illnesses based on the past data applied to the system for the evaluations and analysis. The result shows that the higher accuracy and precision rate for the prediction of several diseases and at the same time low classification error rate using the proposed deep learning model. The proposed article is utilized the chronic illness dataset which consists of depression, fatigue, headache, various body pains symptoms to validate a practical methodology for predicting and handling chronic diseases with partly experimental information.
{"title":"An effective mechanism for early chronic illness detection using multilayer convolution deep learning predictive modelling","authors":"Rohit Daid, Yogesh Kumar, Anish Gupta, Inderpreet Kaur","doi":"10.1109/ICTAI53825.2021.9673393","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673393","url":null,"abstract":"The study aims to predict the chronic disease of different patients using a multilayer convolution deep learning approach, which is a method of deep learning model that treats the input medical data as a vector representation. Additionally, the benefit of multi-layer perceptron is a class of neural networks in a feed-forward way which comprises mainly three layers of processing nodes for the detection of chronic diseases. The proposed system performed an efficient prediction for the diseases based on the mechanism which detects the patient can have a high rate of chronic conditions based on chronic illness. The proposed system accurately predicted that the patients are having a high rate of depressions, fatigue, joint pains, heart diseases, and strokes as chronic illnesses based on the past data applied to the system for the evaluations and analysis. The result shows that the higher accuracy and precision rate for the prediction of several diseases and at the same time low classification error rate using the proposed deep learning model. The proposed article is utilized the chronic illness dataset which consists of depression, fatigue, headache, various body pains symptoms to validate a practical methodology for predicting and handling chronic diseases with partly experimental information.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132622985","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673371
Dhiraj Kumar, M. Prasad, R. Pyare, M. R. Majhi
A mathematical model and a simulation C-program has been developed for the Deep Bed Drying process considering counter-current grain drying as the point of focus.. Diffusion in grain has been considered, and a Single Kernel drying rate equation is used for predicting the variation of moisture content within the grain. The modeling of heat transfer and mass transfer between air and grains in a dryer bed is based on the application of enthalpy balance, mass balance, heat transfer rate, mass transfer rate and the diffusion equation for a single kernel. These equations obtained are highly implicit in nature and need to be solved simultaneously. The results have been generated for drying of corn and are found to be consistent with the expected behaviour. The simulation program developed is fairly general and can be used for any spherical particulate material. The detailed performance prediction results can be used to arrive at an optimum design. Also, optimum performance from an existing dryer design can be obtained by judicious selection of input parameter.
{"title":"Design analysis of continuous counter-current deep bed drying of corn through modeling and simulation and validation with experiment","authors":"Dhiraj Kumar, M. Prasad, R. Pyare, M. R. Majhi","doi":"10.1109/ICTAI53825.2021.9673371","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673371","url":null,"abstract":"A mathematical model and a simulation C-program has been developed for the Deep Bed Drying process considering counter-current grain drying as the point of focus.. Diffusion in grain has been considered, and a Single Kernel drying rate equation is used for predicting the variation of moisture content within the grain. The modeling of heat transfer and mass transfer between air and grains in a dryer bed is based on the application of enthalpy balance, mass balance, heat transfer rate, mass transfer rate and the diffusion equation for a single kernel. These equations obtained are highly implicit in nature and need to be solved simultaneously. The results have been generated for drying of corn and are found to be consistent with the expected behaviour. The simulation program developed is fairly general and can be used for any spherical particulate material. The detailed performance prediction results can be used to arrive at an optimum design. Also, optimum performance from an existing dryer design can be obtained by judicious selection of input parameter.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133341789","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673294
Lipsa Das, Laxmi Ahuja, A. Pandey
Today, social media and email are become a very common and the most effective medium for communication and data transferring which has been greatly affected by undesired spam by sharing unwanted and malicious contents to Internet users which, brings financial losses to organizations as well as become a headache for individual users and leads to decrease in productivity considerably. The spam occupies storage and the communication bandwidth as well as a network threat, when it contains viruses and malicious codes. On an average a user on internet may get 10-20 spam emails per day. For solving spam problems, different counter measures need to deploy to detect and remove these unwanted messages. This paper summarizes the survey of different existing email spam filtering techniques such as how machine and non-machine learning approaches are used to detect incoming unsolicited emails. Each filtering method has their own benefits and demerits. Considering upon the requirements different kind of spam filters, however, here in this research paper, we present the classification, and comparison of various spam email filtering techniques and focusing on the accuracy rate of various existing techniques.
{"title":"Existing Spam Filtering Methods Considering different technique: A review","authors":"Lipsa Das, Laxmi Ahuja, A. Pandey","doi":"10.1109/ICTAI53825.2021.9673294","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673294","url":null,"abstract":"Today, social media and email are become a very common and the most effective medium for communication and data transferring which has been greatly affected by undesired spam by sharing unwanted and malicious contents to Internet users which, brings financial losses to organizations as well as become a headache for individual users and leads to decrease in productivity considerably. The spam occupies storage and the communication bandwidth as well as a network threat, when it contains viruses and malicious codes. On an average a user on internet may get 10-20 spam emails per day. For solving spam problems, different counter measures need to deploy to detect and remove these unwanted messages. This paper summarizes the survey of different existing email spam filtering techniques such as how machine and non-machine learning approaches are used to detect incoming unsolicited emails. Each filtering method has their own benefits and demerits. Considering upon the requirements different kind of spam filters, however, here in this research paper, we present the classification, and comparison of various spam email filtering techniques and focusing on the accuracy rate of various existing techniques.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131774969","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673325
Pushpa Choudhary, S. Yadav, A. Srivastava, Arjun Singh, Smita Sharma
In today’s world, life without technology is not possible. Continuous advancement in patient health monitoring techniques, medical equipment’s or machines and other enhancing technologies is ongoing as per recent trends in specifically healthcare sector in order to reduce human efforts. Taking into consideration the serious nature of the above aforementioned problem, it is necessary to make some major improvements in the communication devices and systems with application-based technology in order to enhance their performance thereby saving medical costs and achieve other major advantages. The principal objective of this paper is to provide a system for remote and secure monitoring of healthcare information of patient suffering from virus and utilizing a mobile device as per the patient requirements. In this paper, a proposed model measure the temperature of the body, respiratory system especially lung sound and breathing activity, which are the main source of symptoms to understand the actual health condition of a person. And data sensed by the IoT sensor device used for measuring the real-time data body temperature, lung sounds, respiratory data, pulse rate and heartbeat.
{"title":"A System for Remote Monitoring of Patient Body Parameters","authors":"Pushpa Choudhary, S. Yadav, A. Srivastava, Arjun Singh, Smita Sharma","doi":"10.1109/ICTAI53825.2021.9673325","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673325","url":null,"abstract":"In today’s world, life without technology is not possible. Continuous advancement in patient health monitoring techniques, medical equipment’s or machines and other enhancing technologies is ongoing as per recent trends in specifically healthcare sector in order to reduce human efforts. Taking into consideration the serious nature of the above aforementioned problem, it is necessary to make some major improvements in the communication devices and systems with application-based technology in order to enhance their performance thereby saving medical costs and achieve other major advantages. The principal objective of this paper is to provide a system for remote and secure monitoring of healthcare information of patient suffering from virus and utilizing a mobile device as per the patient requirements. In this paper, a proposed model measure the temperature of the body, respiratory system especially lung sound and breathing activity, which are the main source of symptoms to understand the actual health condition of a person. And data sensed by the IoT sensor device used for measuring the real-time data body temperature, lung sounds, respiratory data, pulse rate and heartbeat.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"744 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134197790","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673277
Gurinder Singh, Ruchika Gupta, Vidushi Vatsa
Fintech currently ranks among the most thriving sectors in terms of both business growth and job creation. Having emerged as the second-largest fin-tech hub in the world (trailing only the United States), India is also experiencing this ’Fintech Boom.’ Fintech’s wider goal is to meet the unmet financial needs of certain demographic groups that aren’t the main focus markets in mainstream financial services models. It is generally believed that India would be data-rich even before it is financially rich, however, the incidents like Facebook data leak, an alleged Aadhar data breach has brought back the focus on data protection and the urgent need for steps to be taken by all the stakeholders for sustainable growth of Fintech sector. Hence, this paper attempts to explore how India has evolved into a renowned Fintech hub, how this Fintech is perceived to contribute to the broadening of financial inclusion, and what are the barriers to further growth for Fintech firms. This paper also proposes approaches that can help professionals and analysts harness Fintech’s untapped potential in India and also suggested remedial measures for limiting cyber-attacks.
{"title":"A Framework for Enhancing Cyber Security in Fintech Applications in India","authors":"Gurinder Singh, Ruchika Gupta, Vidushi Vatsa","doi":"10.1109/ICTAI53825.2021.9673277","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673277","url":null,"abstract":"Fintech currently ranks among the most thriving sectors in terms of both business growth and job creation. Having emerged as the second-largest fin-tech hub in the world (trailing only the United States), India is also experiencing this ’Fintech Boom.’ Fintech’s wider goal is to meet the unmet financial needs of certain demographic groups that aren’t the main focus markets in mainstream financial services models. It is generally believed that India would be data-rich even before it is financially rich, however, the incidents like Facebook data leak, an alleged Aadhar data breach has brought back the focus on data protection and the urgent need for steps to be taken by all the stakeholders for sustainable growth of Fintech sector. Hence, this paper attempts to explore how India has evolved into a renowned Fintech hub, how this Fintech is perceived to contribute to the broadening of financial inclusion, and what are the barriers to further growth for Fintech firms. This paper also proposes approaches that can help professionals and analysts harness Fintech’s untapped potential in India and also suggested remedial measures for limiting cyber-attacks.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114825531","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673408
B. Wiyono, Desi Eri Eri Kusumaningrum, Dedi Prestiadi
Today, in the era of the industrial revolution 5.0, wherein the people’s lives, information and communication technology are used in all fields, including education. But on the other hand, not all people are ready to use it. The purpose of this study is to reveal the frequency of principals use information and communication technology in managing schools and the variables that influence it. The research used a survey method, with a sample of 81 school principals and teachers who were taken randomly. Questionnaires were used for collecting data. While descriptive statistics and regression were used for analyzing the data. The results showed that the frequency of school principals in using ICT was included in the sufficient category, with the order of use for planning, condition analysis, implementation, outcome evaluation, and process evaluation. Some applications such as WhatsApp, google forms, zoom, google meet, email, video recording, telephone, and audio recording are used widely. The level of effectiveness is included in the effective category. The variable that has a significant effect is the level of education of the principals, while the variables of gender, rank, and work period do not have a significant effect.
{"title":"The Utilization of Information and Communication Technology in School Management, in Relation to the Characteristics of Principals","authors":"B. Wiyono, Desi Eri Eri Kusumaningrum, Dedi Prestiadi","doi":"10.1109/ICTAI53825.2021.9673408","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673408","url":null,"abstract":"Today, in the era of the industrial revolution 5.0, wherein the people’s lives, information and communication technology are used in all fields, including education. But on the other hand, not all people are ready to use it. The purpose of this study is to reveal the frequency of principals use information and communication technology in managing schools and the variables that influence it. The research used a survey method, with a sample of 81 school principals and teachers who were taken randomly. Questionnaires were used for collecting data. While descriptive statistics and regression were used for analyzing the data. The results showed that the frequency of school principals in using ICT was included in the sufficient category, with the order of use for planning, condition analysis, implementation, outcome evaluation, and process evaluation. Some applications such as WhatsApp, google forms, zoom, google meet, email, video recording, telephone, and audio recording are used widely. The level of effectiveness is included in the effective category. The variable that has a significant effect is the level of education of the principals, while the variables of gender, rank, and work period do not have a significant effect.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115115850","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673308
C. Verma, Z. Illés, Veronika Stoffová
The utilization of technology in education has been increasing during the unprecedented time of the Covid-19 pandemics. It has not only affected the opinions of teachers, but also students’ perceptions have been impacted. This paper identified and compared students’ perceptions of Indian and Hungarian universities towards technology use, benefits, and development. A stepwise regression filtered out six significant variables that explained the perception of Indian students ($R^{2}=.91$), and three variables identified the perception of Hungarian students towards technology ($R^{2}=.61$). Indian students’ perception has been recognized with six technology variables: “Sharing of resources expertise and advice”, “ICT tools/techniques promoting workshops policy”, “Up to date learning materials”, “Desktop Computers equipped with internet access”, “E-library”, and “E-Reader”. Three variables such as “Improving analytical skills”, “Download/Browse material”, “High-quality lessons” also impacted the viewpoints of Hungarian students.
{"title":"Prediction of Students’ Perceptions towards Technology’ Benefits, Use and Development","authors":"C. Verma, Z. Illés, Veronika Stoffová","doi":"10.1109/ICTAI53825.2021.9673308","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673308","url":null,"abstract":"The utilization of technology in education has been increasing during the unprecedented time of the Covid-19 pandemics. It has not only affected the opinions of teachers, but also students’ perceptions have been impacted. This paper identified and compared students’ perceptions of Indian and Hungarian universities towards technology use, benefits, and development. A stepwise regression filtered out six significant variables that explained the perception of Indian students ($R^{2}=.91$), and three variables identified the perception of Hungarian students towards technology ($R^{2}=.61$). Indian students’ perception has been recognized with six technology variables: “Sharing of resources expertise and advice”, “ICT tools/techniques promoting workshops policy”, “Up to date learning materials”, “Desktop Computers equipped with internet access”, “E-library”, and “E-Reader”. Three variables such as “Improving analytical skills”, “Download/Browse material”, “High-quality lessons” also impacted the viewpoints of Hungarian students.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"23 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981795","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673220
Pradeep Kushwaha, M. Kumaresan
In the last decades Machine learning techniques are widely used in the field of healthcare systems due to its data processing and analysis capabilities. Machine Learning is a sub domain of artificial intelligence that collects data from various sources and in various format. In Spite of its major capability to handle the huge data still classification of data is still the major difficulty in the field of healthcare. Now a day, many people are facing such kind of vital diseases which need to be identified at the early phase of diseases so that treatment can be start in relevant time. After passing such stage the diseases may be uncurable. This can be possible with the help of various Machine learning technique. Many Machine leaning technique are much more capable to analyze the huge complex medical data, medical reports and medical images in a very less time with accuracy. There are various cases available where many fatal diseases may not be identified by experts. Just like many other field, in healthcare Machine learning algorithms are widely used to tackle such kind of situations. This research article focused on the various field of machine learning that are being used for handling complex data for the purpose of decision making in healthcare system. This paper attempt to provide the brief details about various machine learning approach and review the role of these algorithms in field of healthcare system like diabetic, detection of cancer, brain tumor, bioinformatics and many more.
{"title":"Machine learning algorithm in healthcare system: A Review","authors":"Pradeep Kushwaha, M. Kumaresan","doi":"10.1109/ICTAI53825.2021.9673220","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673220","url":null,"abstract":"In the last decades Machine learning techniques are widely used in the field of healthcare systems due to its data processing and analysis capabilities. Machine Learning is a sub domain of artificial intelligence that collects data from various sources and in various format. In Spite of its major capability to handle the huge data still classification of data is still the major difficulty in the field of healthcare. Now a day, many people are facing such kind of vital diseases which need to be identified at the early phase of diseases so that treatment can be start in relevant time. After passing such stage the diseases may be uncurable. This can be possible with the help of various Machine learning technique. Many Machine leaning technique are much more capable to analyze the huge complex medical data, medical reports and medical images in a very less time with accuracy. There are various cases available where many fatal diseases may not be identified by experts. Just like many other field, in healthcare Machine learning algorithms are widely used to tackle such kind of situations. This research article focused on the various field of machine learning that are being used for handling complex data for the purpose of decision making in healthcare system. This paper attempt to provide the brief details about various machine learning approach and review the role of these algorithms in field of healthcare system like diabetic, detection of cancer, brain tumor, bioinformatics and many more.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834950","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 : 2021-11-10DOI: 10.1109/ICTAI53825.2021.9673296
S. Kaur, Krishnendu Rarhi
The key objective of these works is to deliver a summary of the research that has been done in this field. As the primary objective of this paper, we will look at a recent study carried out during the healthcare sector, in which blockchain technology was used to ensure patient information security and privacy in healthcare records. The information was gathered from a pool of more than 480 participants in the poll and was gathered from the PubMed database from the 2012 year to the present year (2021). Beginning with the retrieval of articles from PubMed that were published between 2012 and the present year, an analysis of these documents regarding blockchain technology in healthcare is carried out. The VOS viewer tool (version 1.6.16) is being used in the following step to analysis the data set in different components, like co-authorship, keywords, and so forth. During the survey, we were able to retrieve a total of 480 publications from the PubMed database that were published between 2012 and the present year and that were about healthcare blockchain technology. As a result of using network analysis and mathematical, users may infer that there is a large amount of potential for working on blockchain in order to ensure higher private information, safety, and honesty.
{"title":"Bibliometric Analysis on Blockchain Technology in Healthcare","authors":"S. Kaur, Krishnendu Rarhi","doi":"10.1109/ICTAI53825.2021.9673296","DOIUrl":"https://doi.org/10.1109/ICTAI53825.2021.9673296","url":null,"abstract":"The key objective of these works is to deliver a summary of the research that has been done in this field. As the primary objective of this paper, we will look at a recent study carried out during the healthcare sector, in which blockchain technology was used to ensure patient information security and privacy in healthcare records. The information was gathered from a pool of more than 480 participants in the poll and was gathered from the PubMed database from the 2012 year to the present year (2021). Beginning with the retrieval of articles from PubMed that were published between 2012 and the present year, an analysis of these documents regarding blockchain technology in healthcare is carried out. The VOS viewer tool (version 1.6.16) is being used in the following step to analysis the data set in different components, like co-authorship, keywords, and so forth. During the survey, we were able to retrieve a total of 480 publications from the PubMed database that were published between 2012 and the present year and that were about healthcare blockchain technology. As a result of using network analysis and mathematical, users may infer that there is a large amount of potential for working on blockchain in order to ensure higher private information, safety, and honesty.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130885352","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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