Deep learning-based artificial intelligence can improve the diagnosis of small bowel obstruction: stratified comparison study and hierarchical Bayesian model

Aitaro Takimoto; Yuichiro Hayashi; Kazuki Nishida; Liu Jiahui; Chiyoe Shirota; Masahiro Oda; Akinari Hinoki; Kojiro Suzuki; Kensaku Mori; Hiroo Uchida

doi:10.1038/s41598-026-57999-w

Deep learning-based artificial intelligence can improve the diagnosis of small bowel obstruction: stratified comparison study and hierarchical Bayesian model

A Aitaro Takimoto Y Yuichiro Hayashi K Kazuki Nishida L Liu Jiahui C Chiyoe Shirota M Masahiro Oda A Akinari Hinoki K Kojiro Suzuki K Kensaku Mori H Hiroo Uchida

View Original

APA MLA Chicago BibTeX RIS

Article Details

Journal Scientific Reports

Volume / Issue Vol. 1, Issue 1

Published June 13, 2026

DOI 10.1038/s41598-026-57999-w

ISSN 2045-2322

Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (10)

A

Aitaro Takimoto

Y

Yuichiro Hayashi

K

Kazuki Nishida

L

Liu Jiahui

C

Chiyoe Shirota

M

Masahiro Oda

A

Akinari Hinoki

K

Kojiro Suzuki

K

Kensaku Mori

H

Hiroo Uchida

Deep learning-based artificial intelligence can improve the diagnosis of small bowel obstruction: stratified comparison study and hierarchical Bayesian model

Article Details

Journal Info

Authors (10)

Related Articles from this Journal

AI models of unstable flow exhibit hallucination

The MCAA-YOLO + XPBI integrated model provides a hybrid intelligent measurement method for predicting the body weight of Hu sheep

Application of iron nano-biofertilizers as a sustainable approach to enhance growth and micronutrient uptake in soybean

Adolescents’ status-dependent public and private conformity to prosocial and antisocial decisions in a public goods game

An explainable hierarchical capsule network framework for supporting expert sensory evaluation of herbal medicines with natural language generation