Author Description

"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 multiple aspects of healthcare, including disease diagnosis, treatment, and personalized medicine. This Special Issue covers a wide range of topics related to the application of machine learning in biomedical engineering, including predictive modelling, image and signal processing, deep learning, drug discovery, biomarker discovery, and medical decision making. 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 significant because it encourages interdisciplinary collaboration between machine learning and biomedical-engineering researchers.