☆ 4.3 Article

Deeplasia: deep learning for bone age assessment validated on skeletal dysplasias

PEDIATRIC RADIOLOGY (2023)

Related references

Note: Only part of the references are listed.

Article Genetics & Heredity

Nosology of genetic skeletal disorders: 2023 revision

Sheila Unger et al.

Summary: The classification of genetic skeletal disorders has been revised in its 11th edition, now including 771 entries associated with 552 genes, reflecting advancements in DNA sequencing technology. The adoption of the dyadic naming system is the most notable change, systematically linking a phenotypic entity to the gene it originates from. This shift is considered a significant improvement, providing more informative and error-resistant nomenclature compared to traditional methods. Despite the adoption of dyadic naming, efforts have been made to maintain a strong connection to the MIM catalog and its historical data. The list of disorders and genes in the Nosology remains valuable for differential diagnosis, bioinformatic analysis, and driving advancements in biology and medicine.

AMERICAN JOURNAL OF MEDICAL GENETICS PART A (2023)

Add to Collection

Article Genetics & Heredity

GestaltMatcher facilitates rare disease matching using facial phenotype descriptors

Tzung-Chien Hsieh et al.

Summary: GestaltMatcher utilizes deep convolutional neural network to improve recognition of rare disorders based on facial morphology, aiding in discovery of new disease genes by detecting similarities among patients with previously unseen syndromes. This approach assists physicians in recognizing characteristic facial morphology associated with monogenic disorders through training on thousands of patient photographs. By developing an encoder based on deep convolutional neural network, GestaltMatcher allows matching of patients even with ultra-rare disorders that were not part of the training set. Combined with mutation data, it can accelerate clinical diagnosis and enable delineation of new phenotypes.

NATURE GENETICS (2022)

Add to Collection

Review Biochemistry & Molecular Biology

AI in health and medicine

Pranav Rajpurkar et al.

Summary: This Review discusses the potential of AI to reshape medicine and make healthcare more accurate, efficient, and accessible. It covers recent progress in medical AI, including advances in medical image analysis, non-image data sources, and human-AI collaboration. The article also addresses technical and ethical challenges, such as data scarcity and racial bias.

NATURE MEDICINE (2022)

Add to Collection

Article Orthopedics

Inferring pediatric knee skeletal maturity from MRI using deep learning

John R. Zech et al.

Summary: This study used deep learning to infer skeletal maturity from knee MRI images in children. The results showed that the model's predictions were comparable to those of radiology residents in terms of accuracy, and the method required less time.

SKELETAL RADIOLOGY (2022)

Add to Collection

Article Pediatrics

Current and emerging artificial intelligence applications for pediatric musculoskeletal radiology

Amaka C. Offiah

Summary: In pediatric radiology, AI is mainly used for bone age assessment, with most research still being in the research domain and not replacing the role of radiologists.

PEDIATRIC RADIOLOGY (2022)

Add to Collection

Article Multidisciplinary Sciences

Accuracy and self-validation of automated bone age determination

D. D. Martin et al.

Summary: This study introduces version 3 of the BoneXpert method for automated determination of bone age from hand X-rays and validates its accuracy and self-validation mechanism. The results show that BoneXpert is more accurate than manual rating and the self-validation mechanism rejects very few images.

SCIENTIFIC REPORTS (2022)

Add to Collection

Review Endocrinology & Metabolism

Factors affecting prepubertal and pubertal bone age progression

Mari Satoh et al.

Summary: Bone age is an important marker of bone maturation, influenced by various hormones including estrogens. Females generally have more advanced bone maturation than males. This study reviews the factors affecting bone age progression, as well as bone maturation and deformities in certain medical conditions.

FRONTIERS IN ENDOCRINOLOGY (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Artificial Intelligence Algorithm Improves Radiologist Performance in Skeletal Age Assessment: A Prospective Multicenter Randomized Controlled Trial

David K. Eng et al.

Summary: This study aimed to compare the accuracy and interpretation time of skeletal age assessment on hand radiograph examinations with and without the use of an AI algorithm as a diagnostic aid. Results showed that using the AI algorithm led to lower mean absolute difference, lower proportions of absolute differences exceeding 12 months and 24 months, and shorter interpretation time.

RADIOLOGY (2021)

Add to Collection

Article Multidisciplinary Sciences

Artificial intelligence system can achieve comparable results to experts for bone age assessment of Chinese children with abnormal growth and development

Fengdan Wang et al.

PEERJ (2020)

Add to Collection

Article Computer Science, Artificial Intelligence

Mimicking the radiologists' workflow: Estimating pediatric hand bone age with stacked deep neural networks

Sven Koitka et al.

MEDICAL IMAGE ANALYSIS (2020)

Add to Collection

Article Medical Informatics

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective

Julia Amann et al.

BMC MEDICAL INFORMATICS AND DECISION MAKING (2020)

Add to Collection

Proceedings Paper Engineering, Biomedical

An Empirical Study on Global Bone Age Assessment

Felipe Torres et al.

15TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

The RSNA Pediatric Bone Age Machine Learning Challenge

Safwan S. Halabi et al.

RADIOLOGY (2019)

Add to Collection

Article Biochemistry & Molecular Biology

Identifying facial phenotypes of genetic disorders using deep learning

Yaron Gurovich et al.

NATURE MEDICINE (2019)

Add to Collection

Review Genetics & Heredity

The evolving therapeutic landscape of genetic skeletal disorders

Ataf Hussain Sabir et al.

ORPHANET JOURNAL OF RARE DISEASES (2019)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

Hand Pose Estimation for Pediatric Bone Age Assessment

Maria Escobar et al.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT VI (2019)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs

David B. Larson et al.

RADIOLOGY (2018)

Add to Collection

Review Pediatrics

Bone Age: A Handy Tool for Pediatric Providers

Ana L. Creo et al.

PEDIATRICS (2017)

Add to Collection

Article Orthopedics

Skeletal development of the hand and wrist: digital bone age companion-a suitable alternative to the Greulich and Pyle atlas for bone age assessment?

Paul M. Bunch et al.

SKELETAL RADIOLOGY (2017)

Add to Collection

Article Multidisciplinary Sciences

Comment: The FAIR Guiding Principles for scientific data management and stewardship

Mark D. Wilkinson et al.

SCIENTIFIC DATA (2016)

Add to Collection

Review Endocrinology & Metabolism

The Use of Bone Age in Clinical Practice - Part 1

David D. Martin et al.

HORMONE RESEARCH IN PAEDIATRICS (2011)

Add to Collection

Review Endocrinology & Metabolism

The Use of Bone Age in Clinical Practice - Part 2

David D. Martin et al.

HORMONE RESEARCH IN PAEDIATRICS (2011)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Validation and Reference Values of Automated Bone Age Determination for Four Ethnicities

Hans Henrik Thodberg et al.

ACADEMIC RADIOLOGY (2010)

Add to Collection

Article Computer Science, Interdisciplinary Applications

The BoneXpert Method for Automated Determination of Skeletal Maturity

Hans Henrik Thodberg et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2009)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Racial Differences in Growth Patterns of Children Assessed on the Basis of Bone Age

Aifeng Zhang et al.

RADIOLOGY (2009)

Add to Collection

Article Engineering, Biomedical

Bone age assessment of children using a digital hand atlas

Arkadiusz Gertych et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2007)

Add to Collection

© Peeref 2019-2024. All rights reserved.