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Neural network prediction of 30-day mortality following primary total hip arthroplasty.

Journal of orthopaedics

Fassihi SC, Mathur A, Best MJ, Chen AZ, Gu A, Quan T, Wang KY, Wei C, Campbell JC, Thakkar SC.
PMID: 34898926
J Orthop. 2021 Nov 25;28:91-95. doi: 10.1016/j.jor.2021.11.013. eCollection 2021.

PURPOSE: The purpose is to utilize an artificial neural network (ANN) model to determine the most important variables in predicting mortality following total hip arthroplasty (THA).METHODS: Patients that underwent primary THA were included from a national database. Demographic, preoperative,...

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Fassihi SC, Mathur A, Best MJ, et al. Neural network prediction of 30-day mortality following primary total hip arthroplasty. J Orthop. 2021;28:91-95doi: 10.1016/j.jor.2021.11.013.
Fassihi, S. C., Mathur, A., Best, M. J., Chen, A. Z., Gu, A., Quan, T., Wang, K. Y., Wei, C., Campbell, J. C., & Thakkar, S. C. (2021). Neural network prediction of 30-day mortality following primary total hip arthroplasty. Journal of orthopaedics, 2891-95. https://doi.org/10.1016/j.jor.2021.11.013
Fassihi, Safa C, et al. "Neural network prediction of 30-day mortality following primary total hip arthroplasty." Journal of orthopaedics vol. 28 (2021): 91-95. doi: https://doi.org/10.1016/j.jor.2021.11.013
Fassihi SC, Mathur A, Best MJ, Chen AZ, Gu A, Quan T, Wang KY, Wei C, Campbell JC, Thakkar SC. Neural network prediction of 30-day mortality following primary total hip arthroplasty. J Orthop. 2021 Nov 25;28:91-95. doi: 10.1016/j.jor.2021.11.013. eCollection 2021. PMID: 34898926; PMCID: PMC8636995.
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Electrifying Engagement in Middle School Science Class: Improving Student Interest Through E-textiles.

Tofel-Grehl C, Fields D, Searle K, Maahs-Fladung C, Feldon D, Gu G, Sun C.
UIID-AD: 4310
2017;1-12. doi: 10.1007/s10956-017-9688-y.

Most interventions with “maker” technologies take place outside of school or out of core area classrooms. However, intervening in schools holds potential for reaching much larger numbers of students and the opportunity to shift instructional dynamics in classrooms. This...

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Tofel-Grehl C, Fields D, Searle K, et al. Electrifying Engagement in Middle School Science Class: Improving Student Interest Through E-textiles. 2017;1-12doi: 10.1007/s10956-017-9688-y.
Tofel-Grehl, C., Fields, D., Searle, K., Maahs-Fladung, C., Feldon, D., Gu, G., & Sun, C. (2017). Electrifying Engagement in Middle School Science Class: Improving Student Interest Through E-textiles. 1-12. https://doi.org/10.1007/s10956-017-9688-y
Tofel-Grehl, C, et al. "Electrifying Engagement in Middle School Science Class: Improving Student Interest Through E-textiles." vol. (2017): 1-12. doi: https://doi.org/10.1007/s10956-017-9688-y
Tofel-Grehl C, Fields D, Searle K, Maahs-Fladung C, Feldon D, Gu G, Sun C. Electrifying Engagement in Middle School Science Class: Improving Student Interest Through E-textiles. 2017;1-12. doi: 10.1007/s10956-017-9688-y. UIID-AD: 4310.
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REU site program to engage undergraduate students in cybersecurity research.

Dong Z, Gu H, Panero MA.
UIID-AD: 4160
2016;

This paper presents the establishment of a research experience for undergraduates (REU) site at New York Institute of Technology (NYIT). The objective of the REU site is to train undergraduates to conduct research and also provide participants with professional...

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Dong Z, Gu H, Panero MA. REU site program to engage undergraduate students in cybersecurity research. 2016;
Dong, Z., Gu, H., & Panero, M. A. (2016). REU site program to engage undergraduate students in cybersecurity research. .
Dong, Z, et al. "REU site program to engage undergraduate students in cybersecurity research." vol. (2016).
Dong Z, Gu H, Panero MA. REU site program to engage undergraduate students in cybersecurity research. 2016; UIID-AD: 4160.
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Showing 8977 to 8979 of 8979 entries