Automated Author ProfileAnderson, Iain
Anderson, Iain
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.4 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Finite element analysis technique incorporates bone remodeling theories and it is extensively used in predicting bone remodeling patterns around the implant. However, a patient-specific finite element model would be more advantageous. Because, the influences of bone geometry, bone strength and gait patterns can be considered in a patient specific model. Therefore, this study leads to create accurate and more realistic algorithm to predict bone remodeling patterns for patients with total hip replacement using patient-specific finite element models. Patient-specific finite element models are being created for a number of patients and then the resulting bone remodeling patterns are being discussed.
Authors
- Arachchi, Shanika ;
- Pitto, Rocco ;
- Anderson, Iain ;
- Shim, Vickie
Finite element analysis technique incorporates bone remodeling theories and it is extensively used in predicting bone remodeling patterns around the implant. However, a patient-specific finite element model would be more advantageous. Because, the influences of bone geometry, bone strength and gait patterns can be considered in a patient specific model. Therefore, this study leads to create accurate and more realistic algorithm to predict bone remodeling patterns for patients with total hip replacement using patient-specific finite element models. Patient-specific finite element models are being created for a number of patients and then the resulting bone remodeling patterns are being discussed.
Authors
- Arachchi, Shanika ;
- Pitto, Rocco ;
- Anderson, Iain ;
- Shim, Vickie