Musa Zaid

TitleVolunteer Faculty
InstitutionThomas Jefferson University
DepartmentFaculty Records
Address1015 Walnut St.
Philadelphia PA 19107
Phone267-339-3500
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    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Cozzarelli NF, Khan IA, Imam N, Klein GR, Levine H, Seidenstein A, Zaid MB, Lonner JH. Robotic-Assisted Total Knee Arthroplasty Has Similar Rates of Prosthetic Noise Generation as Conventional Total Knee Arthroplasty. Arthroplast Today. 2023 Oct; 23:101216. PMID: 37753221.
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    2. Khan IA, Zaid MB, Gold PA, Austin MS, Parvizi J, Bedard NA, Jevsevar DS, Hannon CP, Fillingham YA. Making a Joint Decision Regarding the Timing of Surgery for Elective Arthroplasty Surgery After Being Infected With COVID-19: A Systematic Review. J Arthroplasty. 2022 10; 37(10):2106-2113.e1. PMID: 35533820.
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    3. Shah RF, Zaid MB, Bendich I, Hwang KM, Patterson JT, Bini SA. Optimal Sampling Frequency for Wearable Sensor Data in Arthroplasty Outcomes Research. A Prospective Observational Cohort Trial. J Arthroplasty. 2019 10; 34(10):2248-2252. PMID: 31445866.
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    4. Bini SA, Shah RF, Bendich I, Patterson JT, Hwang KM, Zaid MB. Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial. J Arthroplasty. 2019 10; 34(10):2242-2247. PMID: 31439405.
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