This study proposed a medicine auxiliary diagnosis model based on neural network. The model combines a bidirectional long short-term memory（Bi-LSTM）network and bidirectional encoder representations from transformers (BERT), which can well complete th...
Diabetes is a chronic disease that continues to be a significant and global concern since it affects the entire population's health. It is a metabolic disorder that leads to high blood sugar levels and many other problems such as stroke, kidney failu...
Computational and mathematical methods in medicine
Jan 11, 2022
In rhinoplasty, it is necessary to consider the correlation between the anthropometric indicators of the nasal bone, so that it prevents surgical complications and enhances the patient's satisfaction. The penetrating form of high-energy electromagnet...
We propose a simple anomaly detection method that is applicable to unlabeled time series data and is sufficiently tractable, even for non-technical entities, by using the density ratio estimation based on the state space model. Our detection rule is ...
We examined how individuals' personality relates to various attitudes toward artificial intelligence (AI). Attitudes were organized into two dimensions of affective components (positive and negative emotions) and two dimensions of cognitive component...
Persuasion is a fundamental aspect of how people interact with each other. As robots become integrated into our daily lives and take on increasingly social roles, their ability to persuade will be critical to their success during human-robot interact...
Recent image-generation methods have demonstrated that realistic images can be produced from captions. Despite the promising results achieved, existing caption-based generation methods confront a dilemma. On the one hand, the image generator should b...
In multi-instance learning (MIL), labels are associated with bags rather than the instances in the bag. Most of the previous MIL methods assume that each bag has the actual label in the training set. However, from the process of labeling work, the la...
Data representation learning is one of the most important problems in machine learning. Unsupervised representation learning becomes meritorious as it has no necessity of label information with observed data. Due to the highly time-consuming learning...
In recent years, with the development of medical science and artificial intelligence, research on rehabilitation robots has gained more and more attention, for nearly 10 years in the Web of Science database by journal of rehabilitation robot-related...
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