Journal of Diagnostics Concepts & Practice >
Application of artificial intelligence in medical image data processing for digestive tract tumors
Received date: 2025-07-04
Revised date: 2025-10-30
Online published: 2025-12-25
In recent years, with the rapid development of artificial intelligence (AI) algorithm models, a variety of approaches have emerged, such as convolutional neural networks (CNN) algorithms mainly for image classification, decision trees and support vector machine models for decision classification, attention mechanism models for impro-ving identification accuracy, object detection models for lesion identification and localization in images, and semantic segmentation and instance segmentation models for precise lesion segmentation in images. The deep integration of AI-based CNN with medical imaging has significantly improved the efficiency and accuracy of disease diagnosis. With the improvement of digital medicine, the integration points of image data with AI in disease diagnosis and treatment pathways have further expanded. Besides traditional images, (radiology, ultrasonography, endoscopy, pathology), non-classical images, such as surgical resection specimen images and organoid images, are gradually incorporated into the scope of AI research. The deep involvement of AI helps decode hidden information in multi-dimensional data, conti-nuously transforming disease diagnosis and treatment patterns. In the foreseeable future, the integration of AI algorithms with various disease diagnosis and treatment devices will become powerful tools for disease diagnosis, treatment, and even prediction of development trends.
YANG Ruixin , YU Yingyan . Application of artificial intelligence in medical image data processing for digestive tract tumors[J]. Journal of Diagnostics Concepts & Practice, 2025 , 24(06) : 605 -612 . DOI: 10.16150/j.1671-2870.2025.06.005
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