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Bioengineering
Special Issues
New Technique for Endoscopic Diagnosis in Biomedical Engineering
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New Technique for Endoscopic Diagnosis in Biomedical Engineering

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1066

Special Issue Editor

Dr. Changseok Bang

E-Mail Website
Guest Editor
Institute for Liver and Digestive Diseases, Hallym University, Chuncheon 24252, Republic of Korea
Interests: helicobacter pylori; meta-analysis; medicine; endoscopy; gastroenterology; gastric cancer

Special Issue Information

Dear Colleagues,

This cutting-edge research article explores a new technique for endoscopic diagnosis, which promises to revolutionize the field of gastroenterology. Endoscopy is a critical tool in the diagnosis and treatment of various gastrointestinal disorders, but current techniques are limited by factors such as accuracy, invasiveness, and patient discomfort. The novel approach proposed in this study aims to overcome these limitations by providing a more accurate, less invasive, and patient-friendly method for diagnosing gastrointestinal conditions. By utilizing state-of-the-art technology and methodologies, this technique offers immense potential for improving patient outcomes and advancing the field of endoscopic diagnosis.

Dr. Changseok Bang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • endoscopic diagnosis
  • gastroenterology
  • novel technique
  • precision medicine
  • minimally invasive
  • patient- friendly
  • state-of-the-art technology
  • gastrointestinal disorders
  • diagnostic accuracy
  • research innovation

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Published Papers (1 paper)

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Research

10 pages, 995 KiB  
Article
The Potential Clinical Utility of the Customized Large Language Model in Gastroenterology: A Pilot Study
by Eun Jeong Gong, Chang Seok Bang, Jae Jun Lee, Jonghyung Park, Eunsil Kim, Subeen Kim, Minjae Kimm and Seoung-Ho Choi
Bioengineering 2025, 12(1), 1; https://doi.org/10.3390/bioengineering12010001 - 24 Dec 2024
Viewed by 893
Abstract
Background: The large language model (LLM) has the potential to be applied to clinical practice. However, there has been scarce study on this in the field of gastroenterology. Aim: This study explores the potential clinical utility of two LLMs in the field of [...] Read more.
Background: The large language model (LLM) has the potential to be applied to clinical practice. However, there has been scarce study on this in the field of gastroenterology. Aim: This study explores the potential clinical utility of two LLMs in the field of gastroenterology: a customized GPT model and a conventional GPT-4o, an advanced LLM capable of retrieval-augmented generation (RAG). Method: We established a customized GPT with the BM25 algorithm using Open AI’s GPT-4o model, which allows it to produce responses in the context of specific documents including textbooks of internal medicine (in English) and gastroenterology (in Korean). Also, we prepared a conventional ChatGPT 4o (accessed on 16 October 2024) access. The benchmark (written in Korean) consisted of 15 clinical questions developed by four clinical experts, representing typical questions for medical students. The two LLMs, a gastroenterology fellow, and an expert gastroenterologist were tested to assess their performance. Results: While the customized LLM correctly answered 8 out of 15 questions, the fellow answered 10 correctly. When the standardized Korean medical terms were replaced with English terminology, the LLM’s performance improved, answering two additional knowledge-based questions correctly, matching the fellow’s score. However, judgment-based questions remained a challenge for the model. Even with the implementation of ‘Chain of Thought’ prompt engineering, the customized GPT did not achieve improved reasoning. Conventional GPT-4o achieved the highest score among the AI models (14/15). Although both models performed slightly below the expert gastroenterologist’s level (15/15), they show promising potential for clinical applications (scores comparable with or higher than that of the gastroenterology fellow). Conclusions: LLMs could be utilized to assist with specialized tasks such as patient counseling. However, RAG capabilities by enabling real-time retrieval of external data not included in the training dataset, appear essential for managing complex, specialized content, and clinician oversight will remain crucial to ensure safe and effective use in clinical practice. Full article
(This article belongs to the Special Issue New Technique for Endoscopic Diagnosis in Biomedical Engineering)
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