Machine Learning Technology in Biomedical Engineering

Dear Colleagues,

The Special Issue on "Machine Learning Technology in Biomedical Engineering" aims to provide a platform for researchers to showcase their latest research and findings on the application of machine learning technology in the field of biomedical engineering. The use of machine learning technology in healthcare has been growing rapidly in recent years and has the potential to revolutionize many aspects of healthcare, including disease diagnosis, treatment, and personalized medicine.

The Special Issue will cover a wide range of topics related to the application of machine learning in biomedical engineering, including predictive modeling, image and signal processing, deep learning, drug discovery, biomarker discovery, and medical decision-making. Contributions from interdisciplinary teams combining expertise in machine learning and biomedical engineering are encouraged.

Importance:

The use of machine learning technology in biomedical engineering has significant potential to improve healthcare outcomes and make healthcare more efficient and accessible. By applying machine learning algorithms to large datasets of biomedical information, researchers and healthcare professionals can gain new insights into disease mechanisms, identify new biomarkers for disease, and develop more effective treatments. Machine learning algorithms can also be used to improve medical imaging analysis, automate medical diagnosis and decision-making, and optimize drug-discovery processes.

This Special Issue is important because it provides a platform for researchers to share their latest findings and perspectives on the application of machine learning technology in biomedical engineering, and to encourage interdisciplinary collaboration between machine learning and biomedical engineering researchers. It is an exciting opportunity for researchers to contribute to the development of new technologies and methodologies that have the potential to significantly improve healthcare outcomes

Dr. Hongqing Yu
Dr. Alaa AlZoubi
Dr. Yifan Zhao
Prof. Dr. Hongbo Du
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.