Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.
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| Title: | Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets. |
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| Authors: | Rani R; Department of ECE, Bhagwan Parshuram Institute of Technology, New Delhi, India., Jaiswal G; School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India., Nancy; Department of Computer Science, Indira Gandhi Delhi Technical University for Women, New Delhi, India., Lipika; Department of Computer Science, Indira Gandhi Delhi Technical University for Women, New Delhi, India., Bhushan S; Department of Computing, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia., Ullah F; Department of Computing, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia., Singh P; School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India., Diwakar M; Department of Computer Science Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.; Department of CSE, Graphic Era Hill University, Dehradun, Uttarakhand, India. |
| Source: | Frontiers in medicine [Front Med (Lausanne)] 2025 May 27; Vol. 12, pp. 1502749. Date of Electronic Publication: 2025 May 27 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2296-858X |
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| DOI: | 10.3389/fmed.2025.1502749 |
