LETTER TO THE EDITOR
Response to: Precision in Diagnosis of Liver Fibrosis in MASLD: Machine Learning Based Scores May Be More Accurate Than Conventional NITs
Yasaman Vali,
Corresponding Author
Yasaman Vali
Department of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
Correspondence:
Yasaman Vali ([email protected])
Search for more papers by this author Quentin M. Anstee,
Quentin M. Anstee
Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
Newcastle NIHR Biomedical Research Centre, Upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
Search for more papers by this author Patrick M. Bossuyt,
Patrick M. Bossuyt
Department of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
Search for more papers by this author
Yasaman Vali,
Corresponding Author
Yasaman Vali
Department of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
Correspondence:
Yasaman Vali ([email protected])
Search for more papers by this author Quentin M. Anstee,
Quentin M. Anstee
Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
Newcastle NIHR Biomedical Research Centre, Upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
Search for more papers by this author Patrick M. Bossuyt,
Patrick M. Bossuyt
Department of Epidemiology and Data Science, Amsterdam Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
Search for more papers by this author
First published: 29 March 2025
No abstract is available for this article.
References
- 1Y. Vali, A. M. van Dijk, J. Lee, et al., “Precision in Liver Diagnosis: Varied Accuracy Across Subgroups and the Need for Variable Thresholds in Diagnosis of MASLD,” Liver International 45 (2025): e16240.
- 2J. Lee, M. Westphal, Y. Vali, et al., “Machine Learning Algorithm Improves the Detection of NASH (NAS-Based) and At-Risk NASH: A Development and Validation Study,” Hepatology 78 (2023): 258–271.
- 3R. Soliman, A. Helmy, and G. Shiha, “Precision in Diagnosis of Liver Fibrosis in MASLD: Machine Learning Based Scores May Be More Accurate Than Conventional NITs,” Liver International 45, no. 4 (2025): e70039.
- 4A. Anushiravani, K. Alswat, G. N. Dalekos, et al., “Multicenter Validation of FIB-6 as a Novel Machine Learning Non-invasive Score to Rule out Liver Cirrhosis in Biopsy-Proven MAFLD,” European Journal of Gastroenterology & Hepatology 35, no. 11 (2023): 1284–1288.
