Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Privacy-aware community infrastructureResearch graph
References from Artificial intelligence–assisted diagnosis of pediatric supracondylar humerus fractures: a deep learning–based clinical decision support model. Local targets link to admitted publications; unresolved targets remain external evidence.
Overview of the contemporary management of supracondylar humeral fractures in children.
10.1007/s00590-021-02932-2 · 2021 · External reference
Management of supracondylar fractures of the humerus in children.
1959 · External reference
Classifications in brief: the Gartland classification of supracondylar humerus fractures.
10.1007/s11999-014-4033-8 · 2015 · External reference
A clinical study of percutaneous Kirschner wire fixation in pediatric supracondylar humeral fractures with medial column impaction: surgical technique and outcomes.
10.1186/s13018-025-06275-0 · 2025 · External reference
Diagnostic value of artificial intelligence-based software for the detection of pediatric upper extremity fractures.
10.1007/s00330-025-11947-w · 2026 · External reference
Accuracy of emergency room physicians’ interpretation of elbow fractures in children.
10.3928/01477447-20081201-23 · 2008 · External reference
Black and white: how good are clinicians at diagnosing elbow injuries from paediatric elbow radiographs alone?
10.1136/emermed-2024-214047 · 2024 · External reference
Missed elbow trauma in children: value of radiograph assessment in an emergency department. a review of 136 cases.
2005 · External reference
Automatic hip fracture identification and functional subclassification with deep learning.
10.1148/ryai.2020190023 · 2020 · External reference
Pediatric supracondylar fractures of the distal humerus.
10.1007/s12178-008-9027-2 · 2008 · External reference
Assessing deep learning artificial intelligence support for detecting elbow fractures in the pediatric emergency department.
10.1016/j.ejrad.2025.112498 · 2026 · External reference
Artificial intelligence in fracture detection: a systematic review and meta-analysis.
10.1148/radiol.211785 · 2022 · External reference
STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies.
10.1136/bmj.h5527 · 2015 · External reference
Ultrasonographic evaluation of the elbow in infants and young children after suspected trauma.
10.2106/00004623-199412000-00006 · 1994 · External reference
Distal humeral epiphyseal separation in young children: an often-missed fracture-radiographic signs and ultrasound confirmatory diagnosis.
10.2214/ajr.14.12788 · 2015 · External reference
Short-term management outcomes of supracondylar fractures of the humerus and their associated factors in children managed at Mulago National Referral Hospital.
2022 · External reference
The clip limit decision of contrast limited adaptive histogram equalization for X-ray images using Fuzzy logic.
10.9717/kmms.2015.18.7.806 · 2015 · External reference
Improving radiographic fracture recognition performance and efficiency using artificial intelligence.
10.1148/radiol.210937 · 2022 · External reference
Diagnostic accuracy and failure mode analysis of a deep learning algorithm for the detection of cervical spine fractures.
10.3174/ajnr.a7179 · 2021 · External reference
Pediatric elbow trauma.
10.1097/00006565-199712000-00021 · 1997 · External reference
External validation of an artificial intelligence solution for the detection of elbow fractures and joint effusions in children.
10.1016/j.diii.2023.09.008 · 2024 · External reference
Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.
10.1097/md.0000000000038503 · 2024 · External reference
Use of deep learning model for paediatric elbow radiograph binomial classification: initial experience, performance and lessons learnt.
10.4103/singaporemedj.smj-2022-078 · 2025 · External reference
Impact of deep learning on pediatric elbow fracture detection: a systematic review and meta-analysis.
10.1007/s00068-025-02779-w · 2025 · External reference
Artificial intelligence diagnostic accuracy in fracture detection from plain radiographs and comparing it with clinicians: a systematic review and meta-analysis.
10.1016/j.crad.2024.04.009 · 2024 · External reference
Flexing ChatGPT-4o’s diagnostic muscle: detection of fractures in the ossifying pediatric elbow on radiographs.
10.3390/diagnostics15222882 · 2025 · External reference
Impact of test set composition on AI performance for pediatric radiograph appendicular skeleton fracture detection.
10.1148/radiol.250540 · 2026 · External reference
Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs.
10.1007/s00330-019-06167-y · 2019 · External reference
Development and validation of a deep learning model using convolutional neural networks to identify scaphoid fractures in radiographs.
10.1001/jamanetworkopen.2021.6096 · 2021 · External reference
The Gartland classification for expediting supracondylar humerus fracture triage: a collaborative approach to structured reporting between pediatric radiologists and orthopedists.
10.1016/j.clinimag.2024.110118 · 2024 · External reference
The prevalence effect in a laboratory environment: changing the confidence ratings.
10.1016/j.acra.2006.10.003 · 2007 · External reference
Low target prevalence is a stubborn source of errors in visual search tasks.
10.1037/0096-3445.136.4.623 · 2007 · External reference
