Latest AI and machine learning research in surveys for healthcare professionals.
Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks, while such success relies heavily on the assumption that the training and future data must be of the same data distribution. However, this assumption may not hold in many real-world applications. Model calibration is required via data re-collection and label annotation, which is generally very exp...
This paper clarifies why bias cannot be completely mitigated in Machine Learning (ML) and proposes an end-to-end methodology to translate the ethical principle of justice and fairness into the practice of ML development as an ongoing agreement with stakeholders. The pro-ethical iterative process presented in the paper aims to challenge asymmetric power dynamics in the fairness decision making with...
In a society centered on hyper-connectivity, information sharing is crucial, but it must be ensured that each piece of information is viewed only by l...
BACKGROUND: When introducing new equipment like robotic surgical systems, it is essential to ensure that surgeons have the basic skills before operati...
Since 2016, we have witnessed the tremendous growth of artificial intelligence+visualization (AI+VIS) research. However, existing survey articles on A...
Uncertainty is inherent in machine learning methods, especially those for camouflaged object detection aiming to finely segment the objects concealed ...
In safety-critical automatic systems, safety can be compromised if operators lack engagement. Effective detection of undesirable engagement states can...
In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the imm...
BACKGROUND: Resources are increasingly spent on artificial intelligence (AI) solutions for medical applications aiming to improve diagnosis, treatment...
The use of artificial intelligence (AI) in dentistry is rapidly evolving and could play a major role in a variety of dental fields. This study assesse...
Characterizing uncertainty in machine learning models has recently gained interest in the context of machine learning reliability, robustness, safety,...
As novelty is a core value in science, a reliable approach to measuring the novelty of scientific documents is critical. Previous novelty measures how...
Blowout fractures are a common type of facial injury that requires accurate measurement of the fracture area for proper treatment planning. This syste...
In this article, evolving and incremental value iteration (VI) frameworks are constructed to address the discrete-time zero-sum game problem. First, t...
Zero-shot detection (ZSD) aims to locate and classify unseen objects in pictures or videos by semantic auxiliary information without additional traini...
Learning about one’s implicit bias is crucial for improving one’s cultural competency and thereby reducing health inequity. To evaluate bias among med...
The questionnaire method has always been an important research method in psychology. The increasing prevalence of multidimensional trait measures in p...
Protein function prediction is a major challenge in the field of bioinformatics which aims at predicting the functions performed by a known protein. M...
Human activity recognition (HAR) is an important research problem in computer vision. This problem is widely applied to building applications in human...
Artificial intelligence-based models and robust computational methods have expedited the data-to-knowledge trajectory in precision medicine. Although ...