ArticleDiagnostics (Basel, Switzerland)2020
Improving Prosthetic Selection and Predicting BMD from Biometric Measurements in Patients Receiving Total Hip Arthroplasty.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 33 citations in OpenAlex.
- Sex and age specific bone mineral density trends in Sri Lankan adults support the need for normative reference data.Frontiers in endocrinology · 2026Article
- An Experimental and Virtual Approach to Hip Revision Prostheses.Diagnostics (Basel, Switzerland) · 2022Article
- The role of bone mineral density and cartilage volume to predict knee cartilage degeneration.European journal of translational myology · 2022Article
- Symmetry breaking and effects of nutrient walkway in time-dependent bone remodeling incorporating poroelasticity.Biomechanics and modeling in mechanobiology · 2022Article
- Machine Learning and Regression Analysis to Model the Length of Hospital Stay in Patients with Femur Fracture.Bioengineering (Basel, Switzerland) · 2022Article
- Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson's Disease.Sensors (Basel, Switzerland) · 2022Article
- CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone.Diagnostics (Basel, Switzerland) · 2022Article
- Testing soft tissue radiodensity parameters interplay with age and self-reported physical activity.European journal of translational myology · 2021Article
- Psoas Muscle Index Defined by Computer Tomography Predicts the Presence of Postoperative Complications in Colorectal Cancer Surgery.Medicina (Kaunas, Lithuania) · 2021Article
- Health technology assessment through Six Sigma Methodology to assess cemented and uncemented protheses in total hip arthroplasty.European journal of translational myology · 2021Article
- Toward Predicting Motion Sickness Using Virtual Reality and a Moving Platform Assessing Brain, Muscles, and Heart Signals.Frontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
Abstract
There are two surgical approaches to performing total hip arthroplasty (THA): a cemented or uncemented type of prosthesis. The choice is usually based on the experience of the orthopaedic surgeon and on parameters such as the age and gender of the patient. Using machine learning (ML) techniques on quantitative biomechanical and bone quality data extracted from computed tomography, electromyography and gait analysis, the aim of this paper was, firstly, to help clinicians use patient-specific biomarkers from diagnostic exams in the prosthetic decision-making process. The second aim was to evaluate patient long-term outcomes by predicting the bone mineral density (BMD) of the proximal and distal parts of the femur using advanced image processing analysis techniques and ML. The ML analyses were performed on diagnostic patient data extracted from a national database of 51 THA patients using the Knime analytics platform. The classification analysis achieved 93% accuracy in choosing the type of prosthesis; the regression analysis on the BMD data showed a coefficient of determination of about 0.6. The start and stop of the electromyographic signals were identified as the best predictors. This study shows a patient-specific approach could be helpful in the decision-making process and provide clinicians with information regarding the follow up of patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.