Articles

Artificial Intelligence and Informatics - Original Article

Meta-research on reporting guidelines for artificial intelligence: are authors and reviewers encouraged enough in radiology, nuclear medicine, and medical imaging journals?

Burak Koçak
Ali Keleş
Fadime Köse

Diagn Interv Radiol 0; 0: 0-0 [e-Pub] DOI: 10.4274/dir.2024.232604 PMID:38375627

Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study

Bo Liu
Hao Liu
Lequan Zhang
Yancheng Song
Shifeng Yang
Ziwen Zheng
Junjiang Zhao
Feng Hou
Jian Zhang

Diagn Interv Radiol 2022; 28: 29-38 DOI: 10.5152/dir.2021.21600

Machine learning analysis of adrenal lesions: preliminary study evaluating texture analysis in the differentiation of adrenal lesions

Canan Altay
Işıl Başara Akın
Abdullah Hakan Özgül
Süleyman Cem Adıyaman
Abdullah Serkan Yener
Mustafa Seçil

Diagn Interv Radiol 2023; 29: 234-243 DOI: 10.5152/dir.2022.21266 PMID:36987841

Prediction of carcinogenic human papillomavirus types in cervical cancer from multiparametric magnetic resonance images with machine learning-based radiomics models

Okan İnce
Emre Uysal
Görkem Durak
Suzan Önol
Binnur Dönmez Yılmaz
Şükrü Mehmet Ertürk
Hakan Önder

Diagn Interv Radiol 2023; 29: 460-468 DOI: 10.4274/dir.2022.221335 PMID:36994859

Artificial Intelligence and Informatics - Review

Artificial intelligence in diagnostic ultrasonography

Oğuz Dicle

Diagn Interv Radiol 2023; 29: 40-45 DOI: 10.4274/dir.2022.211260 PMID:36959754

Key concepts, common pitfalls, and best practices in artificial intelligence and machine learning: focus on radiomics

Burak Koçak

Diagn Interv Radiol 2022; 28: 450-462 DOI: 10.5152/dir.2022.211297

Abdominal Imaging - Original Article

Tubular gastric adenocarcinoma: machine learning-based CT texture analysis for predicting lymphovascular and perineural invasion

Aytül Hande Yardımcı
Burak Koçak
Ceyda Turan Bektaş
İpek Sel
Enver Yarıkkaya
Nevra Dursun
Hasan Bektaş
Çiğdem Usul Afşar
Rıza Umar Gürsu
Özgür Kılıçkesmez

Diagn Interv Radiol 2020; 26: 515-522 DOI: 10.5152/dir.2020.19507

Head and Neck Radiology - Review

Diagnostic performance of radiomics using machine learning algorithms to predict MGMT promoter methylation status in glioma patients: a meta-analysis

Huan Huang
Fei-fei Wang
Shigang Luo
Guangxiang Chen
Guangcai Tang

Diagn Interv Radiol 2021; 27: 716-724 DOI: 10.5152/dir.2021.21153

About Journal

Forms

Useful Links