Medical knowledge graphs (MKGs) are the basis for intelligent health care, and they have
been in use in a variety of intelligent medical applications. Thus, understanding the research …

Abstract Domain tuning pre-trained language models (PLMs) with task-specific prompts
have achieved great success in different domains. By using cloze-style language prompts to …

Expert system is the most commonly used method for auxiliary diagnosis of dairy cow
diseases, which is complex to build and usually difficult for non-professional farmers to …

With a mortality rate of 5.4 million lives worldwide every year and a healthcare cost of more
than 16 billion dollars in the USA alone, sepsis is one of the leading causes of hospital …

The purpose of this study is to identify additional clinical features for sepsis detection
through the use of a novel mechanism for interpreting black-box machine learning models …

Sepsis is a life-threatening condition with a high mortality rate. Early prediction and
treatment are the most effective strategies for increasing survival rates. This paper proposes …

Background Sepsis is a syndrome involving multi-organ dysfunction, and the mortality in
sepsis patients correlates with the number of lesioned organs. Precise prognosis models …

Learning-based shadow detection methods have achieved an impressive performance,
while these works still struggle on complex scenes, especially ambiguous soft shadows. To …

Background Most infectious diseases are caused by viruses, fungi, bacteria and parasites.
Their ability to easily infect humans and trigger large-scale epidemics makes them a public …

The construction of medical knowledge graphs (MKGs) is steadily progressing from manual
to automatic methods, which inevitably introduce noise, which could impair the performance …