IEEE Journal of Translational Engineering in Health and Medicine’s unique aim is to publish original work in the intersection of engineering and clinical translation. The journal’s focus is interdisciplinary collaborations between researchers, healthcare providers, and industry and aims to publish results and best practices from these translational efforts.

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In an era where technology is expanding at a rapid rate and the needs for medical application of these technologies has never been greater, the intersection between engineering, medicine and biology is a critical place to be. The IEEE Engineering in Medicine and Biology Society is well-positioned to serve as a central gathering point for both of these major disciplines.

Early Access Articles

Design and In Vitro Validation of an Orthopaedic Drill Guide for Femoral Stem Revision in Total Hip Arthroplasty 1978 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Design and In Vitro Validation of an Orthopaedic Drill Guide for Femoral Stem Revision in Total Hip Arthroplasty

Abstract:

Objective: Cemented total hip arthroplasty (THA) demonstrates superior survival rates compared to uncemented procedures. Nevertheless, most younger patients opt for uncemented THA, as removing well-fixed bone cement in the femur during revisions is complex, particularly the distal cement plug. This removal procedure often increases the risk of femoral fracture or ...

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Compliant Intramedullary Stems for Joint Reconstruction 1978 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Compliant Intramedullary Stems for Joint Reconstruction

Abstract:

The longevity of current joint replacements is limited by aseptic loosening, which is the primary cause of non-infectious failure for hip, knee, and ankle arthroplasty. Aseptic loosening is typically caused either by osteolysis from particulate wear, or by high shear stresses at the bone-implant interface from over-constraint. Our objective was ...

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Deep Learning-based, multiclass approach to cancer classification on liquid biopsy data 1978 2560 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Deep Learning-based, multiclass approach to cancer classification on liquid biopsy data

Abstract:

Objective: The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development ...

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Updates

The IEEE Journal of Translational Engineering in Health and Medicine Volume 9 was recently published.