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Experimental animal models may aid discriminating genetic vs. environmental effects and designing innovative therapeutic approaches.
While results based on these models may aid policy makers in identifying larger areas of elevated exposure risk, they often do not differentiate the proportion of population exposure attributable to different polluting sources (e.g. traffic or industrial).
One day, such models may aid the surgeon in preoperative planning or in the engineering of implant design, ultimately resulting in an improved clinical outcome.
The prediction models may aid in patient-physician shared decision-making when they are considering warfarin therapy.
Our experience also indicates that constraint-based models may aid in the interpretation of such high-throughput datasets, potentially helping to identify false negative results.
These models may aid the clinician in the decision-making process regarding clinical admission, early prevention, early clinical diagnosis, and application of clinical therapies.
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Computational approaches involving finite element (FE) modeling may aid to determine their influence.
The theoretical model may aid in evaluating the efficacy of anti-metastatic therapies, thus benefiting the design of prospective clinical trials.
Our model may aid to develop the respective studies and to reproducibly demonstrate the functional relevance of the investigated treatment regimen for renal and vascular regeneration.
The model may aid in a flexible exchange and analysis of electrocardiogram information.
This animal model may aid in future studies aiming at prevention of aseptic loosening of hip prosthesis and reflect some aspects of the pathogenesis involved.
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