Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty?

Hassan M.K. Ghomrawi; Carol A. Mancuso; Alejandro Gonzalez Della Valle; Michael Alexiades; Charles Cornell; Thomas Sculco; Mathias Bostrom; David Mayman; Robert G. Marx; Geoffrey Westrich; Alvin I. Mushlin

doi:10.1097/CORR.0000000000001255

Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty?

Hassan M.K. Ghomrawi^*, Carol A. Mancuso, Alejandro Gonzalez Della Valle, Michael Alexiades, Charles Cornell, Thomas Sculco, Mathias Bostrom, David Mayman, Robert G. Marx, Geoffrey Westrich, Alvin I. Mushlin

^*Corresponding author for this work

Surgery

Research output: Contribution to journal › Letter › peer-review

Original language	English (US)
Pages (from-to)	1378-1379
Number of pages	2
Journal	Clinical orthopaedics and related research
Volume	478
Issue number	6
DOIs	https://doi.org/10.1097/CORR.0000000000001255
State	Published - Jun 1 2020

ASJC Scopus subject areas

Surgery
Orthopedics and Sports Medicine

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10.1097/CORR.0000000000001255

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Ghomrawi, H. M. K., Mancuso, C. A., Della Valle, A. G., Alexiades, M., Cornell, C., Sculco, T., Bostrom, M., Mayman, D., Marx, R. G., Westrich, G., & Mushlin, A. I. (2020). Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty? Clinical orthopaedics and related research, 478(6), 1378-1379. https://doi.org/10.1097/CORR.0000000000001255

@article{3a1ba642e9004a30b10388263d3a9762,

title = "Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty?",

author = "Ghomrawi, {Hassan M.K.} and Mancuso, {Carol A.} and {Della Valle}, {Alejandro Gonzalez} and Michael Alexiades and Charles Cornell and Thomas Sculco and Mathias Bostrom and David Mayman and Marx, {Robert G.} and Geoffrey Westrich and Mushlin, {Alvin I.}",

year = "2020",

month = jun,

day = "1",

doi = "10.1097/CORR.0000000000001255",

language = "English (US)",

volume = "478",

pages = "1378--1379",

journal = "Clinical orthopaedics and related research",

issn = "0009-921X",

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}

Ghomrawi, HMK, Mancuso, CA, Della Valle, AG, Alexiades, M, Cornell, C, Sculco, T, Bostrom, M, Mayman, D, Marx, RG, Westrich, G & Mushlin, AI 2020, 'Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty?', Clinical orthopaedics and related research, vol. 478, no. 6, pp. 1378-1379. https://doi.org/10.1097/CORR.0000000000001255

Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty? / Ghomrawi, Hassan M.K.; Mancuso, Carol A.; Della Valle, Alejandro Gonzalez et al.
In: Clinical orthopaedics and related research, Vol. 478, No. 6, 01.06.2020, p. 1378-1379.

Research output: Contribution to journal › Letter › peer-review

TY - JOUR

T1 - Reply to the Letter to the Editor

T2 - Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty?

AU - Ghomrawi, Hassan M.K.

AU - Mancuso, Carol A.

AU - Della Valle, Alejandro Gonzalez

AU - Alexiades, Michael

AU - Cornell, Charles

AU - Sculco, Thomas

AU - Bostrom, Mathias

AU - Mayman, David

AU - Marx, Robert G.

AU - Westrich, Geoffrey

AU - Mushlin, Alvin I.

PY - 2020/6/1

Y1 - 2020/6/1

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U2 - 10.1097/CORR.0000000000001255

DO - 10.1097/CORR.0000000000001255

M3 - Letter

C2 - 32271173

AN - SCOPUS:85084696074

SN - 0009-921X

VL - 478

SP - 1378

EP - 1379

JO - Clinical orthopaedics and related research

JF - Clinical orthopaedics and related research

IS - 6

ER -

Reply to the Letter to the Editor: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences from Total Joint Arthroplasty?

ASJC Scopus subject areas

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