Translational engineering is a rapidly growing field of study that bridges the gap between engineering and healthcare, providing solutions to real-world problems in both sectors. Through the application of engineering principles to clinical and healthcare problems, translational engineering seeks to improve the quality of patient care, reduce costs, and enable the development of new treatments and technologies. Translational engineering can provide new insights into the design of medical devices, inform the use of artificial intelligence in healthcare, and enable the development of new therapies. Additionally, translational engineering can help to address disparities in access to healthcare, provide improved diagnostic tools, and develop innovative solutions for delivering personalised care.
The Gold Open Access IEEE Journal of Translational Engineering in Health and Medicine champions the translation of engineering methods into clinical practice. This is achieved by publishing studies reporting on evidence-based practice. When translating engineering methods into clinical practice, it is important to base decisions on evidence-based practice. IEEE JTEHM seeks manuscripts that report the use of the best available engineering methods to make clinical decisions and inform healthcare practice.
The Editorial Board of the IEEE Journal of Translational Engineering in Health and Medicine is composed of experts in biomedical engineering and clinical medicine. It is critical to have experts in both disciplines when translating engineering methods into clinical practice. The IEEE Journal of Translational Engineering in Health and Medicine seeks manuscripts that report on studies on the translation process, specifically on how translation can be implemented safely and effectively but also on resources that are needed for successful translation.
When translating engineering methods into clinical practice, it is important to consider potential risks and develop strategies for mitigating them. The risk associated with the use of medical devices but also risks associated with maintaining patient privacy are of great interest to the IEEE Journal of Translational Engineering in Health and Medicine. Studies that report on the creation of systems for monitoring and responding to any potential risks are of specific interest.
Medical device regulatory requirements require devices to be continuously monitored in their use and to evaluate their benefit in health outcomes. However, it is also important to monitor and evaluate the outcomes of the translation process. This can help to identify any areas that need to be improved and ensure that the translation process is successful.
In order to support the translation of engineering from the lab to the clinic, it is important to have a detailed description of the analysis methods and data. The IEEE Journal of Translational Engineering in Health and Medicine encourages the sharing of methods and data, including through peer-reviewed publications in the journal but also through open-access datasets. Open-access datasets are also a great way to share analysis methods and data, as they allow anyone to access and use the data. This ensures that findings are accurately represented and makes it more transparent for researchers to compare their findings to those of other researchers and to collaborate on new research projects.
While simulation studies involving a dataset to simulate real-world medical scenarios can be valid and be an essential step in developing analysis methods, publications simply reporting on data analysis using online datasets often do not test in real-world medical scenarios to assess if the translation from the lab to the clinic is possible. The validity of the results of such publications depends on the accuracy of the dataset and the methods used to simulate the scenarios. The IEEE Journal of Translational Engineering in Health and Medicine is keen to publish studies that have ensured that the dataset is representative of the real-world and that the methods used to simulate the scenarios are reliable, reproducible and translatable to real-world medical scenarios.
The IEEE Journal of Translational Engineering in Health and Medicine is keen to receive submissions from authors on studies that have embraced the themes above. The journal is keen to disseminate this information in an open-access format to ensure the study results have the maximum impact on healthcare provision and human health.