Analysis of Research Hotspots and Trends in the Application of Artificial Intelligence in Gastrointestinal Diseases Field

With the development of artificial intelligence, technological advancements have widely permeated the medical field, exerted a significant influence and played a crucial role in the diagnosis and treatment of gastrointestinal diseases. Artificial intelligence can quickly learn from expert experience, achieve wide-scale replication, work continuously and self-update. It can effectively alleviate the pain caused by gastrointestinal diseases and even help patients recover. This also significantly reduces the pressure on both doctors and patients. Doctors and experts can utilize artificial intelligence and 5G communication technology to remotely control surgeries, and precisely remove tumors, polyps and other issues within patients' bodies. This method can also enable experts to perform surgeries remotely, solving the problems of patients' mobility difficulties and the long distance between the two locations. Moreover, the quality of the surgeries has also been improved through technologies such as artificial intelligence. Based on the research results and the success rate of the surgeries, it has been concluded that through the application of artificial intelligence technology, long-distance surgeries can be conducted, and the results are basically the same as those of traditional surgical methods.

Authors

Institutions

Publication Details

Journal
Theoretical and Natural Science
Published
2025-09-03
DOI
https://doi.org/10.54254/2753-8818/2025.ad26484
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Research Hotspots and Trends in the Application of Artificial Intelligence in Gastrointestinal Diseases Field

Zhi Li
1 links
Theoretical and Natural Science
Radiomics and Machine Learning in Medical Imaging
article

Analysis of Research Hotspots and Trends in the Application of Artificial Intelligence in Gastrointestinal Diseases Field

Zhi Li
article en

Abstract

With the development of artificial intelligence, technological advancements have widely permeated the medical field, exerted a significant influence and played a crucial role in the diagnosis and treatment of gastrointestinal diseases. Artificial intelligence can quickly learn from expert experience, achieve wide-scale replication, work continuously and self-update. It can effectively alleviate the pain caused by gastrointestinal diseases and even help patients recover. This also significantly reduces the pressure on both doctors and patients. Doctors and experts can utilize artificial intelligence and 5G communication technology to remotely control surgeries, and precisely remove tumors, polyps and other issues within patients' bodies. This method can also enable experts to perform surgeries remotely, solving the problems of patients' mobility difficulties and the long distance between the two locations. Moreover, the quality of the surgeries has also been improved through technologies such as artificial intelligence. Based on the research results and the success rate of the surgeries, it has been concluded that through the application of artificial intelligence technology, long-distance surgeries can be conducted, and the results are basically the same as those of traditional surgical methods.

Theoretical and Natural ScienceVol. 134(1)
University of Science and Technology (YE)
Openalex Percentile: Top 67%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.