Abstract: Liver disease is diagnosed automatically using artificial intelligence (AI) models trained, tested and validated on liver disease datasets representing clinical or diagnostic measurements encapsulated in biochemical markers like albumin as well as enzymes implicated in metabolic processes. The responses of the trained AI models to new clinical diagnostic input could drive clinical decision-making support. Ultimately, the trained AI models could be packaged into an automated liver disease diagnosis module and merged with a repertoire of modules for the automated diagnosis of a wide range of health conditions within the context of a comprehensive AI-driven healthcare system.
Keywords: Deep Learning (DL), Artificial Intelligence (AI), Liver Disease, Cirrhosis of the Liver, Albumin, Artificial Neural Network (ANN), TensorFlow, Healthcare System, Disease Diagnosis and Prediction.
|
DOI:
10.17148/IJARCCE.2025.14213
