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

MLA

Ronnie Sebro, and Cynthia De la Garza-Ramos. “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.” Osteoporosis and Sarcopenia, vol. 8, no. 3, Sept. 2022, pp. 112–22. EBSCOhost, https://doi.org/10.1016/j.afos.2022.09.002.

APA

Ronnie Sebro, & Cynthia De la Garza-Ramos. (2022). 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. Osteoporosis and Sarcopenia, 8(3), 112–122. https://doi.org/10.1016/j.afos.2022.09.002

Chicago

Ronnie Sebro, and Cynthia De la Garza-Ramos. 2022. “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.” Osteoporosis and Sarcopenia 8 (3): 112–22. doi:10.1016/j.afos.2022.09.002.