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Author Spotlight: Establishing MASLD Cell Models for Investigating Disease Mechanisms and the Lipid-Lowering Effects of Koumiss
Published on: July 19, 2024
Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: Transforming diagnosis and
Pablo Guillermo Hernández-Almonacid1, Ximena Marín-Quintero2
1Department of Internal Medicine, National University of Colombia, Bogota 111311, Colombia. pghernandezalm@gmail.com.
Abstract:
Metabolic dysfunction-associated steatotic liver disease (MASLD) is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events. Given its significant clinical impact, the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes. Over the past decade, the integration of artificial intelligence (AI) into gastroenterology has led to transformative advancements in medical practice. AI represents a major step towards personalized medicine, offering the potential to enhance diagnostic accuracy, refine prognostic assessments, and optimize treatment strategies. Its applications are rapidly expanding. This article explores the emerging role of AI in the management of MASLD, emphasizing its ability to improve clinical prediction, enhance the diagnostic performance of imaging modalities, and support histopathological confirmation. Additionally, it examines the development of AI-guided personalized treatments, where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.
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