{"title":"使用卷积神经网络预测早期慢性肾脏疾病","authors":"N. Pareek, Deepika Soni, S. Degadwala","doi":"10.1109/ICAAIC56838.2023.10141322","DOIUrl":null,"url":null,"abstract":"Significant numbers of individuals all around the globe are afflicted with chronic kidney disease (CKD). Preventing further problems and slowing the course of CKD requires early detection and treatment. To better detect early-stage CKD, this research suggests an AI-based smart expert system to analyze patient clinical data. The system makes predictions about CKD's early stages using a machine learning algorithm that takes as input data such as demographics, laboratory results, and clinical factors. Better patient outcomes and lower healthcare expenditures are two possible benefits of the suggested method to increase CKD diagnosis rates.","PeriodicalId":267906,"journal":{"name":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Early Stage Chronic Kidney Disease Prediction using Convolution Neural Network\",\"authors\":\"N. Pareek, Deepika Soni, S. Degadwala\",\"doi\":\"10.1109/ICAAIC56838.2023.10141322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Significant numbers of individuals all around the globe are afflicted with chronic kidney disease (CKD). Preventing further problems and slowing the course of CKD requires early detection and treatment. To better detect early-stage CKD, this research suggests an AI-based smart expert system to analyze patient clinical data. The system makes predictions about CKD's early stages using a machine learning algorithm that takes as input data such as demographics, laboratory results, and clinical factors. Better patient outcomes and lower healthcare expenditures are two possible benefits of the suggested method to increase CKD diagnosis rates.\",\"PeriodicalId\":267906,\"journal\":{\"name\":\"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAAIC56838.2023.10141322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAAIC56838.2023.10141322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Early Stage Chronic Kidney Disease Prediction using Convolution Neural Network
Significant numbers of individuals all around the globe are afflicted with chronic kidney disease (CKD). Preventing further problems and slowing the course of CKD requires early detection and treatment. To better detect early-stage CKD, this research suggests an AI-based smart expert system to analyze patient clinical data. The system makes predictions about CKD's early stages using a machine learning algorithm that takes as input data such as demographics, laboratory results, and clinical factors. Better patient outcomes and lower healthcare expenditures are two possible benefits of the suggested method to increase CKD diagnosis rates.