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Assist. Noura Ahmed Ali Ahmed Hanafy :: Publications: |
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| Title: | Machine Learning-Based Classification of Liver Steatosis Using Bioimpedance Spectral Features |
| Authors: | Noura Hanafy |
| Year: | 2025 |
| Keywords: | Not Available |
| Journal: | Not Available |
| Volume: | Not Available |
| Issue: | Not Available |
| Pages: | Not Available |
| Publisher: | Not Available |
| Local/International: | Local |
| Paper Link: | Not Available |
| Full paper | Noura Ahmed Ali Ahmed Hanafy_Abstract _Noura Hanafy.pdf |
| Supplementary materials | Not Available |
| Abstract: |
Liver steatosis, or fatty liver disease, is an increasingly prevalent global health issue that can lead to severe complications like cirrhosis and carcinoma. While liver biopsy is the diagnostic "gold standard," it is invasive, time-consuming, and carries risks. Standard non-invasive methods like BIA often face limitations in accuracy due to physiological variability, low data variability, and the "curse of dimensionality" when handling high-dimensional spectral data. |
