{
  "abstract": "Background Metabolic dysfunction–associated steatotic liver disease (MASLD) is an increasingly prevalent cause of chronic liver disease, closely linked with obesity, diabetes, and other metabolic risk factors. Despite its rising burden, early detection in primary care remains inconsistent. Artificial intelligence (AI) offers a potential solution by enabling efficient identification of high-risk individuals. This study aimed to evaluate the impact of an AI-assisted risk stratification model on early detection of MASLD in a primary care setting.Methods A 12-month prospective study was conducted involving 150 adult patients with metabolic risk factors, including obesity, type 2 diabetes mellitus, and dyslipidaemia. Patients were stratified into low-, moderate-, and high-risk groups using an AI algorithm incorporating body mass index, blood glucose, lipid profile, and liver enzyme values. High-risk individuals underwent targeted ultrasound screening for hepatic steatosis. Outcomes, including identification of high-risk patients and MASLD detection rates, were compared with standard care practicesResults Implementation of the AI model increased identification of high-risk patients from 40% to 72%. Detection of MASLD improved from 22% to 41%. Targeted screening also reduced unnecessary imaging in low-risk individuals by 30%, optimizing use of clinical resources. The intervention was well integrated into the routine workflow and was not associated with any adverse events.Conclusions AI-assisted risk stratification significantly improves early detection of MASLD and enhances resource allocation in primary care. This approach supports the integration of AI into routine hepatology practice and highlights its potential as a scalable strategy for managing metabolic liver disease. Further studies are needed to evaluate long-term outcomes and refine predictive models.",
  "authors": [
    {
      "affiliations": [
        "Rawal Institute of Health Sciences, Pakistan"
      ],
      "name": "Usman Ghani"
    },
    {
      "affiliations": [
        "MOTH, Pakistan"
      ],
      "name": "Abrar Hussain Azad"
    }
  ],
  "title": "IDDF2026-ABS-0453 Artificial intelligence (AI) driven early detection of metabolic dysfunction associated steatotic liver disease (MASLD) in primary care",
  "uid": "746d4b81-57fe-5c77-bc48-b09abaebcb1d"
}