Artificial Intelligence in Medical Imaging - Baishideng Publishing Group

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Welcome to the Artificial Intelligence in Medical Imaging

Machine-learning requires pre-defined feature inputs which are then extracted in order to classify target image characteristics.

Artificial intelligence -assisted endoscopy and data processing are the currently demonstrated uses for Artificial intelligence.

The flow diagram of radiomics.

Use of computer aided detection to identify polyp, outlined with a blue box.

Nomogram based on the radiomics feature and clinical predictors.

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Criteria for assessing the diagnostic significance of modern methods of imaging gastrointestinal diseases in practical gastroenterology

Featured Articles More >>

Criteria for assessing the diagnostic significance of modern... 2024-09-26
Preoperative perineural invasion in rectal cancer based on d... 2024-09-26
Evaluation of computer aided detection during colonoscopy am... 2023-12-08
Radiomics: Status quo and future challenges 2022-12-28
Advances and horizons for artificial intelligence of endosco... 2022-06-28

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INDEXING/ABSTRACTING

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GUIDELINES FOR AUTHORS

Artificial Intelligence in Medical Imaging (AIMI, Artif Intell Med Imaging) is a high-quality, online, open-access, single-blind peer-reviewed journal published by the Baishideng Publishing Group. AIMI accepts both solicited and unsolicited manuscripts. Articles published in AIMI are high-quality, clinical and basic, influential research articles by established academic authors as well as new researchers. The paramount objective of AIMI is to showcase and promote distinguished research in the field of artificial intelligence in medical imaging, to help advance development of this field. The types of articles published in the AIMI include Editorial, Opinion Review, Frontier, Review, Minireview, Clinical Research, Basic Study, Systematic Review, Meta-analysis, Evidence-based Medicine, Field of Vision, Clinical Guidelines, Letter to the Editor, and Case Report. Submit here >>

2024 Published Issues

Editors-in-Chief

Jun Shen, MD, Professor, (E-mail: shenjun@mail.sysu.edu.cn) Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China

Indexing/Abstracting

The AIMI is now abstracted and indexed in Reference Citation Analysis, China Science and Technology Journal Database.

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There is currently no impact factor.

ISSN

2644-3260 (online)

Current Issue

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Contents Volume 5 Issue 1 September 28, 2024

Retrospective Study

Preoperative perineural invasion in rectal cancer based on deep learning radiomics stacking nomogram: A retrospective study