[HTML][HTML] Evaluation of bone age in children: a mini-review

F Cavallo, A Mohn, F Chiarelli, C Giannini - Frontiers in Pediatrics, 2021 - frontiersin.org
Bone age represents a common index utilized in pediatric radiology and endocrinology
departments worldwide for the definition of skeletal maturity for medical and non-medical …

Applications of artificial intelligence in forensic sciences: C urrent potential benefits, limitations and perspectives

N Galante, R Cotroneo, D Furci, G Lodetti… - International Journal of …, 2023 - Springer
In recent years, new studies based on artificial intelligence (AI) have been conducted in the
forensic field, posing new challenges and demonstrating the advantages and disadvantages …

Performance of a deep-learning neural network model in assessing skeletal maturity on pediatric hand radiographs

DB Larson, MC Chen, MP Lungren, SS Halabi… - Radiology, 2018 - pubs.rsna.org
Purpose To compare the performance of a deep-learning bone age assessment model
based on hand radiographs with that of expert radiologists and that of existing automated …

[HTML][HTML] Fully automated deep learning system for bone age assessment

H Lee, S Tajmir, J Lee, M Zissen, BA Yeshiwas… - Journal of digital …, 2017 - Springer
Skeletal maturity progresses through discrete phases, a fact that is used routinely in
pediatrics where bone age assessments (BAAs) are compared to chronological age in the …

Deep learning for automated skeletal bone age assessment in X-ray images

C Spampinato, S Palazzo, D Giordano, M Aldinucci… - Medical image …, 2017 - Elsevier
Skeletal bone age assessment is a common clinical practice to investigate endocrinology,
genetic and growth disorders in children. It is generally performed by radiological …

Paediatric bone age assessment using deep convolutional neural networks

VI Iglovikov, A Rakhlin, AA Kalinin… - Deep Learning in Medical …, 2018 - Springer
Skeletal bone age assessment is a common clinical practice to diagnose endocrine and
metabolic disorders in child development. In this paper, we describe a deep learning …

A shapelet transform for time series classification

J Lines, LM Davis, J Hills, A Bagnall - Proceedings of the 18th ACM …, 2012 - dl.acm.org
The problem of time series classification (TSC), where we consider any real-valued ordered
data a time series, presents a specific machine learning challenge as the ordering of …

Computer-aided diagnosis: how to move from the laboratory to the clinic

B Van Ginneken, CM Schaefer-Prokop, M Prokop - Radiology, 2011 - pubs.rsna.org
Computer-aided diagnosis (CAD), encompassing computer-aided detection and
quantification, is an established and rapidly growing field of research. In daily practice …

[HTML][HTML] Bone age assessment methods: a critical review

AM Mughal, N Hassan, A Ahmed - Pakistan journal of medical …, 2014 - ncbi.nlm.nih.gov
The bone age of a child indicates his/her level of biological and structural maturity better
than the chronological age calculated from the date of birth. Radiography of the hand & wrist …

[HTML][HTML] Bone age assessment with various machine learning techniques: a systematic literature review and meta-analysis

AL Dallora, P Anderberg, O Kvist, E Mendes… - PloS one, 2019 - journals.plos.org
BACKGROUND The assessment of bone age and skeletal maturity and its comparison to
chronological age is an important task in the medical environment for the diagnosis of …