PUMA

academical publication management
collect, organize, and share publications

( en | de )

 

Disambiguation of "Kim, Deok Won"

Author of the publication

copydeleteadd this publication to your clipboard
Risk Prediction of Femoral Neck Osteoporosis Using Machine Learning and Conventional Methods.

, , , and . IWANN (2), volume 7903 of Lecture Notes in Computer Science, page 181-188. Springer, (2013)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Robin Kimmel University of Stuttgart

King Cho Wong University of Stuttgart

Seongkyeong Kim University of Stuttgart

Kim Glumann University of Stuttgart

Kim Müller University of Stuttgart

 

Other publications of authors with the same name

Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor., , , , , and . IEEE Trans. Biomed. Engineering, 62 (11): 2568-2575 (2015)Screening for pre-diabetes using support vector machine model., , , , and . EMBC, page 2472-2475. IEEE, (2014)The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment., , , , , and . Med. Biol. Engineering and Computing, 57 (3): 677-687 (2019)Risk Prediction of Femoral Neck Osteoporosis Using Machine Learning and Conventional Methods., , , and . IWANN (2), volume 7903 of Lecture Notes in Computer Science, page 181-188. Springer, (2013)EHS subjects do not perceive RF EMF emitted from smart phones better than non-EHS subjects., , , , and . EMBC, page 2190-2193. IEEE, (2012)Osteoporosis risk prediction using machine learning and conventional methods., , , and . EMBC, page 188-191. IEEE, (2013)Screening for Prediabetes Using Machine Learning Models., , , , , , , and . Comp. Math. Methods in Medicine, (2014)Mortality prediction of rats in acute hemorrhagic shock using machine learning techniques., , , , , and . Med. Biol. Engineering and Computing, 51 (9): 1059-1067 (2013)Comparison of survival predictions for rats with hemorrhagic shocks using an artificial neural network and support vector machine., , , , , , and . EMBC, page 91-94. IEEE, (2011)Classification of serous ovarian tumors based on microarray data using multicategory support vector machines., , , , and . EMBC, page 3430-3433. IEEE, (2014)