- Support vector machines are superior to principal components analysis for selecting the optimal bones’ CT attenuations for opportunistic screening for osteoporosis using CT scans of the foot or ankle
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Sebro R, Garza-Ramos CDl
- KMID: 2537739
- Osteoporos Sarcopenia.
- 2022 Sep;8(3):112-122.
- doi: 10.1016/j.afos.2022.09.002
Objectives: To use the computed tomography (CT) attenuation of the foot and ankle bones for opportunistic screening for osteoporosis. Methods: Retrospective study of 163 consecutive patients from a tertiary care academic... -
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- Prospective Study of Central versus Peripheral Obesity in Total Knee Arthroplasty
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Armstrong , Morris TR, Sebro R, Israelite , Kamath AF
- KMID: 2438112
- Knee Surg Relat Res.
- 2018 Dec;30(4):319-325.
- doi: 10.5792/ksrr.18.025
PURPOSE: Body mass index (BMI) is often used to predict surgical difficulty in patients receiving total knee arthroplasty (TKA); however, BMI neglects variation in the central versus peripheral distribution of... -
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- Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data
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Purkayastha S, Xiao Y, Jiao Z, Thepumnoeysuk R, Halsey K, Wu J, Tran TML, Hsieh B, Choi JW, Wang D, Vallières M, Wang R, Collins S, Feng X, Feldman M, Zhang PJ, Atalay M, Sebro R, Yang L, Fan Y, Liao Wh, Bai HX
- KMID: 2518657
- Korean J Radiol.
- 2021 Jul;22(7):1213-1224.
- doi: 10.3348/kjr.2020.1104
Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials... -
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