Development and validation of a machine learning-derived radiomics model for diagnosis of osteoporosis and osteopenia using quantitative computed tomography

[11] Adams JE(2020)Radiomics for classification of bone mineral loss: a machine learning study Diagn Interv Imaging 101 e104-e107

[12] Armbrecht G(2020)Deep learning of lumbar spine X-ray for osteopenia and osteoporosis screening: a multicenter retrospective cohort study Bone 140 6241-6250

[13] Augat P(2017)Computational radiomics system to decode the radiographic phenotype Cancer Res 77 1226-1238

[14] Bogado CE(2020)Reliability and prognostic value of radiomic features are highly dependent on choice of feature extraction platform Eur Radiol 30 4844-4852

[15] Bouxsein ML(2005)Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy IEEE Trans Pattern Anal Mach Intell 27 3-17

[16] Tagliafico AS(2013)High-resolution bone imaging for osteoporosis diagnostics and therapy monitoring using clinical MDCT and MRI Curr Med Chem 20 20101115-64

[17] Cea M(2012)Osteoporosis imaging: state of the art and advanced imaging Radiology 263 56-e171

[18] Rossi F(2013)Computerised analysis of osteoporotic bone patterns using texture parameters characterising bone architecture Br J Radiol 86 e165-430

[19] Valdora F(2014)Trabecular bone structure analysis of the spine using clinical MDCT: can it predict vertebral bone strength? J Bone Miner Metab 32 422-185

[20] Bignotti B(2021)Radiomics based on lumbar spine magnetic resonance imaging to detect osteoporosis Acad Radiol 28 3529-2523

[11] Adams JE(2020)Radiomics for classification of bone mineral loss: a machine learning study Diagn Interv Imaging 101 e104-e107

[12] Armbrecht G(2020)Deep learning of lumbar spine X-ray for osteopenia and osteoporosis screening: a multicenter retrospective cohort study Bone 140 6241-6250

[13] Augat P(2017)Computational radiomics system to decode the radiographic phenotype Cancer Res 77 1226-1238

[14] Bogado CE(2020)Reliability and prognostic value of radiomic features are highly dependent on choice of feature extraction platform Eur Radiol 30 4844-4852

[15] Bouxsein ML(2005)Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy IEEE Trans Pattern Anal Mach Intell 27 3-17

[16] Tagliafico AS(2013)High-resolution bone imaging for osteoporosis diagnostics and therapy monitoring using clinical MDCT and MRI Curr Med Chem 20 20101115-64

[17] Cea M(2012)Osteoporosis imaging: state of the art and advanced imaging Radiology 263 56-e171

[18] Rossi F(2013)Computerised analysis of osteoporotic bone patterns using texture parameters characterising bone architecture Br J Radiol 86 e165-430

[19] Valdora F(2014)Trabecular bone structure analysis of the spine using clinical MDCT: can it predict vertebral bone strength? J Bone Miner Metab 32 422-185

[20] Bignotti B(2021)Radiomics based on lumbar spine magnetic resonance imaging to detect osteoporosis Acad Radiol 28 3529-2523