Medical Concept Normalization (MCN) is a crucial process for deep information extraction and natural language processing tasks, which plays a vital role in biomedical research. Although MCN in English has achieved significant research achievements, C...
This comprehensive systematic review critically analyzes the current progress and challenges in automating transtibial prosthesis alignment. The manual identification of alignment changes in prostheses has been found to lack reliability, necessitatin...
Pediatric obesity can drastically heighten the risk of cardiometabolic alterations later in life, with insulin resistance standing as the cornerstone linking adiposity to the increased cardiovascular risk. Puberty has been pointed out as a critical s...
Dose prediction is a crucial step in automated radiotherapy planning for liver cancer. Several deep learning-based approaches for dose prediction have been proposed to enhance the design efficiency and quality of radiotherapy plan. However, these app...
The lack of annotated medical images limits the performance of deep learning models, which usually need large-scale labelled datasets. Few-shot learning techniques can reduce data scarcity issues and enhance medical image analysis speed and robustnes...
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a severe condition affecting millions worldwide, leading to numerous annual deaths. The absence of significant symptoms in its early stages promotes high underdiagnosis rates for the affecte...
The advent of computer vision technology and increased usage of video cameras in clinical settings have facilitated advancements in movement disorder analysis. This review investigated these advancements in terms of providing practical, low-cost solu...
Artificial intelligence is constantly revolutionizing biomedical research and healthcare management. Disease comorbidity is a major threat to the quality of life for susceptible groups, especially middle-aged and elderly patients. The presence of mul...