Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:46:15.531499Z
Paper Citation Record · LEDGER
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models
As of 20 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2411.10345.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
12 of 12 outbound references displayed
- verified exact0
- verified fuzzy12
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 01658cf6-b6bb-4d4c-9e07-abe34fbd44c6 · outbound
This paper cites Intelligent Bone Age Assessment: An Automated System to Detect a Bone Growth Problem Using Convolutional Neural Networks with Attention Mechanism.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Intelligent Bone Age Assessment: An Automated System to Detect a Bone Growth Problem Using Convolutional Neural Networks with Attention Mechanism
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.830882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f9dac3b0-fd2a-44a0-a092-dd1c1951e95c · outbound
This paper cites Radiographic Atlas of Skeletal Development of the Hand and Wrist; Stanford University Press: Palo Alto, CA, USA, 1959.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Radiographic Atlas of Skeletal Development of the Hand and Wrist; Stanford University Press: Palo Alto, CA, USA, 1959
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.803006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 827a7306-305c-417c-a5b4-7bb85f5104eb · outbound
This paper cites Assessment of skeletal maturity and prediction of adult height (TW2 method); Saunders: London, UK, 2001; pp.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Assessment of skeletal maturity and prediction of adult height (TW2 method); Saunders: London, UK, 2001; pp
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.777383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d7082391-9f7c-462e-942d-06862416975b · outbound
This paper cites Paediatric bone age assessment using deep convolutional neural networks.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Paediatric bone age assessment using deep convolutional neural networks
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.759090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 35392a26-9d3f-462d-836f-66279ed2f422 · outbound
This paper cites Shufflenet v2: Practical Guidelines for Efficient CNN Architecture Design.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Shufflenet v2: Practical Guidelines for Efficient CNN Architecture Design
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.739018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a32b1b6a-52cb-485c-a236-b63a293711af · outbound
This paper cites Using Convolutional Neural Networks and Transfer Learning for Bone Age Classification.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Using Convolutional Neural Networks and Transfer Learning for Bone Age Classification
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.719824Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 47380cbb-aa32-4234-9187-22af9bf6714d · outbound
This paper cites Deep learning for automated skeletal bone age assessment in X -ray images.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Deep learning for automated skeletal bone age assessment in X -ray images
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.699085Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 39b33296-b016-4721-85a2-bd5dda32535c · outbound
This paper cites Very deep convolutional networks for large-scale image recognition.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Very deep convolutional networks for large-scale image recognition
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.676253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 42ed46f0-4659-430d-b425-13bbb9224f42 · outbound
This paper cites Fully automated deep learning system for bone age assessment.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Fully automated deep learning system for bone age assessment
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.651703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a6a01682-c989-474f-bb92-42f4184e89eb · outbound
This paper cites Xception: Deep Learning with Depthwise Separable Convolutions.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Xception: Deep Learning with Depthwise Separable Convolutions
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.624835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 17287137-f6f0-4397-8754-1f8554852f55 · outbound
This paper cites Fully automated bone age assessment on large-scale hand X-ray dataset.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Fully automated bone age assessment on large-scale hand X-ray dataset
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.605266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9d87c1e4-3c94-425a-bc24-c5c8f96cac15 · outbound
This paper cites Rethinking the Inception Architecture for Computer Vision.
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models Rethinking the Inception Architecture for Computer Vision
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T19:46:15.585940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.