Naman Bansal, P. Arora, D. Sharma, K. D. Gupta, Chandana Kuntala
{"title":"Image Analysis for E-Healthcare Systems using Multi-Biometric Recognition Model","authors":"Naman Bansal, P. Arora, D. Sharma, K. D. Gupta, Chandana Kuntala","doi":"10.1109/InCACCT57535.2023.10141736","DOIUrl":null,"url":null,"abstract":"With the dawn of e-Healthcare systems, Medical Record Management has become an important research problem. The storage and organization of medical records have made relatively little progress in a world of constantly emerging new technologies and continuous innovation. Many hospitals keep the records on paper, which raises many challenges, including but not limited to a significant amount of time for searching and retrieving a specific record, high maintenance costs, lack of backup, and limited security. Although the inclusion of technology has made this task far more efficient and secure, there is still much that can be done to improve it. This paper proposes a double index-based approach for mapping medical records directly to a patient’s biometrics which would take advantage of the uniqueness of biometrics to identify a patient. The proposed multi-biometric model achieves an accuracy of 97% and an F 1 score of 0.9814.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/InCACCT57535.2023.10141736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the dawn of e-Healthcare systems, Medical Record Management has become an important research problem. The storage and organization of medical records have made relatively little progress in a world of constantly emerging new technologies and continuous innovation. Many hospitals keep the records on paper, which raises many challenges, including but not limited to a significant amount of time for searching and retrieving a specific record, high maintenance costs, lack of backup, and limited security. Although the inclusion of technology has made this task far more efficient and secure, there is still much that can be done to improve it. This paper proposes a double index-based approach for mapping medical records directly to a patient’s biometrics which would take advantage of the uniqueness of biometrics to identify a patient. The proposed multi-biometric model achieves an accuracy of 97% and an F 1 score of 0.9814.