A survey of machine learning in kidney disease diagnosis
Applications of Machine learning (ML) in health informatics have gained increasing attention. The timely diagnosis of kidney disease and the subsequent immediate response to it are of the cases that shed light on the substantial role of ML diagnostic algorithms. ML in Kidney Disease Diagnosis (MLKDD...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827022000937 |
| _version_ | 1828165374396334080 |
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| author | Jaber Qezelbash-Chamak Saeid Badamchizadeh Kourosh Eshghi Yasaman Asadi |
| author_facet | Jaber Qezelbash-Chamak Saeid Badamchizadeh Kourosh Eshghi Yasaman Asadi |
| author_sort | Jaber Qezelbash-Chamak |
| collection | DOAJ |
| description | Applications of Machine learning (ML) in health informatics have gained increasing attention. The timely diagnosis of kidney disease and the subsequent immediate response to it are of the cases that shed light on the substantial role of ML diagnostic algorithms. ML in Kidney Disease Diagnosis (MLKDD) is an active research topic that aims at assisting physicians with computer-aided systems. Various investigations have tried to test the feasibility, applicability, and superiority of different ML methods over each other. However, lacking a holistic survey for this literature has always been a noticeable shortcoming. Hence, this paper provides a comprehensive literature review of ML utilizations in kidney disease diagnosis by introducing two different frameworks, one for MLs, classifying various aspects of kidney disease diagnosis, and the other is the framework of medical sub-fields related to MLKDD. In addition, research gaps are discovered, and future study directions are discussed. |
| first_indexed | 2024-04-12T01:43:45Z |
| format | Article |
| id | doaj.art-36fa1a38570742d39eaeb09409ac225e |
| institution | Directory Open Access Journal |
| issn | 2666-8270 |
| language | English |
| last_indexed | 2024-04-12T01:43:45Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Machine Learning with Applications |
| spelling | doaj.art-36fa1a38570742d39eaeb09409ac225e2022-12-22T03:53:08ZengElsevierMachine Learning with Applications2666-82702022-12-0110100418A survey of machine learning in kidney disease diagnosisJaber Qezelbash-Chamak0Saeid Badamchizadeh1Kourosh Eshghi2Yasaman Asadi3Department of Industrial and Systems Engineering, University of Florida, FL, USA; Corresponding author.Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, IranDepartment of Industrial Engineering, Sharif University of Technology, Tehran, IranDepartment of Industrial Engineering, Shahid Bahonar University of Kerman, Kerman, IranApplications of Machine learning (ML) in health informatics have gained increasing attention. The timely diagnosis of kidney disease and the subsequent immediate response to it are of the cases that shed light on the substantial role of ML diagnostic algorithms. ML in Kidney Disease Diagnosis (MLKDD) is an active research topic that aims at assisting physicians with computer-aided systems. Various investigations have tried to test the feasibility, applicability, and superiority of different ML methods over each other. However, lacking a holistic survey for this literature has always been a noticeable shortcoming. Hence, this paper provides a comprehensive literature review of ML utilizations in kidney disease diagnosis by introducing two different frameworks, one for MLs, classifying various aspects of kidney disease diagnosis, and the other is the framework of medical sub-fields related to MLKDD. In addition, research gaps are discovered, and future study directions are discussed.http://www.sciencedirect.com/science/article/pii/S2666827022000937Machine learningData miningDisease diagnosisKidneyHealthcareMedical informatic |
| spellingShingle | Jaber Qezelbash-Chamak Saeid Badamchizadeh Kourosh Eshghi Yasaman Asadi A survey of machine learning in kidney disease diagnosis Machine Learning with Applications Machine learning Data mining Disease diagnosis Kidney Healthcare Medical informatic |
| title | A survey of machine learning in kidney disease diagnosis |
| title_full | A survey of machine learning in kidney disease diagnosis |
| title_fullStr | A survey of machine learning in kidney disease diagnosis |
| title_full_unstemmed | A survey of machine learning in kidney disease diagnosis |
| title_short | A survey of machine learning in kidney disease diagnosis |
| title_sort | survey of machine learning in kidney disease diagnosis |
| topic | Machine learning Data mining Disease diagnosis Kidney Healthcare Medical informatic |
| url | http://www.sciencedirect.com/science/article/pii/S2666827022000937 |
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