International Journal of Biomedical Engineering and Technology
Scope & Guideline
Fostering Collaboration for the Future of Healthcare
Introduction
Aims and Scopes
- Biomedical Imaging and Signal Processing:
Research in this area encompasses techniques for image acquisition, processing, and analysis, particularly using deep learning and machine learning methods to improve diagnostic accuracy and treatment planning. - Wearable and Implantable Medical Devices:
This scope includes the design and development of smart devices for health monitoring, rehabilitation, and disease management, integrating IoT and AI technologies to enhance patient care. - Rehabilitation Engineering:
Focus on the development of devices and systems that assist in the rehabilitation of patients with physical disabilities, including robotics and virtual reality applications. - Diagnostic and Prognostic Tools:
Research aimed at improving diagnostic methods through advanced algorithms and imaging techniques, including the use of AI in predicting disease progression and treatment outcomes. - Biomaterials and Tissue Engineering:
Exploration of new biomaterials for medical applications, focusing on their design, functionality, and integration with biological tissues for applications in regenerative medicine. - Computational Modelling and Simulation:
Utilization of computational methods to model biological systems, enabling better understanding of physiological processes and the development of predictive models for clinical applications.
Trending and Emerging
- Artificial Intelligence and Machine Learning:
There is a clear trend towards the application of AI and machine learning across various biomedical applications, including diagnostics, imaging analysis, and predictive modelling, highlighting the growing importance of these technologies in healthcare. - Telemedicine and Remote Monitoring:
The COVID-19 pandemic has accelerated research in telehealth technologies, including remote patient monitoring systems that utilize wearable sensors and mobile health applications. - Advanced Imaging Techniques:
Emerging techniques in imaging, such as deep learning-enhanced MRI and CT scans, are gaining traction, indicating a shift towards more precise and efficient diagnostic tools. - Robotics in Surgery and Rehabilitation:
The integration of robotics in surgical procedures and rehabilitation therapies is on the rise, showcasing innovation in enhancing surgical precision and patient recovery. - Nanotechnology in Medicine:
Research into the applications of nanotechnology for drug delivery, imaging, and therapeutic interventions is emerging as a significant focus, reflecting advances in material science and engineering.
Declining or Waning
- Traditional Statistical Methods:
The reliance on conventional statistical methods for data analysis in biomedical research appears to be waning, with a notable shift towards machine learning and AI-driven approaches that offer more robust predictive capabilities. - Basic Biomechanics Studies:
Studies focusing on basic biomechanical principles without the integration of advanced technologies such as AI or machine learning are becoming less frequent, as the field increasingly emphasizes interdisciplinary approaches. - Invasive Medical Procedures:
Research centered on invasive techniques is declining as non-invasive and minimally invasive technologies gain traction, reflecting a broader trend towards patient-centered care and improved outcomes.
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