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Research Progress on the Application of Radiomics and Deep Learning in Liver Fibrosis.

Yi Dang1, Wenjing Li1, Zhao Liu1

  • 1Department of Radiology, The First Hospital of Lanzhou University, Lanzhou 730000, China.

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|February 26, 2026
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Summary

Artificial intelligence (AI), including radiomics and deep learning (DL), offers non-invasive methods for diagnosing liver fibrosis (LF). These advanced techniques show promise in improving early detection and treatment strategies for liver diseases.

Keywords:
deep learningliver fibrosismultimodal fusionradiomics

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Oncology

Background:

  • Liver fibrosis (LF) is a critical stage in liver disease progression, leading to cirrhosis and cancer.
  • Accurate early diagnosis is essential for effective treatment and improved patient outcomes.
  • Conventional liver biopsy has limitations including invasiveness and variability.

Purpose of the Study:

  • To review recent advancements in radiomics and deep learning (DL) for liver fibrosis (LF) diagnosis.
  • To analyze the utility of multimodal imaging in LF assessment.
  • To highlight the potential of AI in overcoming diagnostic challenges and advancing precision medicine for LF.

Main Methods:

  • Review of current literature on radiomics and DL applications in liver fibrosis.
  • Analysis of multimodal imaging techniques such as MRI, CT, and ultrasound.
  • Evaluation of AI models for LF diagnosis, staging, prognosis, and etiological differentiation.

Main Results:

  • Radiomics and DL show significant potential as non-invasive tools for LF diagnosis.
  • Multimodal imaging integrated with AI enhances diagnostic accuracy.
  • AI-driven strategies offer improved interpretability and integration capabilities.

Conclusions:

  • AI, radiomics, and DL represent promising non-invasive approaches for liver fibrosis evaluation.
  • Continued advancements in AI and multimodal imaging integration are crucial for overcoming current challenges.
  • These technologies hold potential for precision medicine in liver disease management.