Latest AI and machine learning research in surveys for healthcare professionals.
Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias, and learning discriminating boundaries between the minority and majority classes could be challenging. To address the class distribution imbalance i...
Recent innovations within the field of robotic surgery have particular relevance to colorectal surgery. Although a robotic approach has been associated with satisfactory outcomes, there remains a wide variation in levels of adoption. In particular, this study focuses on patient positioning, docking, and table placement, with the intent of understanding the strength of opinion of colorectal surgeon...
Cardiovascular magnetic resonance (CMR) derived ventricular volumes and function guide clinical decision-making for various cardiac pathologies. We ai...
In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harr...
With the development of society, China pays more and more attention to cultural education. The teaching method of introducing ideological and politica...
Based on the risk management of exposure to foreign exchange assets and liabilities and the application of financial derivatives, this paper provides ...
A recurrent neural network (RNN) is a machine learning model that learns the relationship between elements of an input series, in addition to inferrin...
This survey article is concerned with the emergence of vision augmentation AI tools for enhancing the situational awareness of first responders (FRs) ...
The quality of financial decision-making is very important to the future development of an enterprise, but it is often affected by the completeness of...
In this paper, we adopt the algorithms of linguistic feature Rong and sparse self-learning neural network to conduct an in-depth study and analysis of...
The purpose is to improve employees' initiative and innovation performance and further improve the overall organizational efficiency of colleges. From...
As the most prevalent and deadly malignancy, brain tumors have a dismal survival rate when they are at their most hazardous. Using mostly traditional ...
Fuzzy associative classifiers (FACs) have recently received considerable attention in the data mining community due to their ability to address the im...
Leadership behavior has been emphasized as one of the most important influencing factors in the innovation process. Leaders can encourage subordinates...
The study aims to explore the influence of big data on college students' learning methods of ideological and political education (IPE) under artificia...
Due to concealed initial symptoms, many diabetic patients are not diagnosed in time, which delays treatment. Machine learning methods have been applie...
In this paper, we introduce a new type of interpolation operators by using Lagrange polynomials of degree r, which can be regarded as feedforward neur...
This exploration aims to promote the development of urbanization in China and improve the utilization rate of urban resources. First, intensive theory...
Background Preexisting indexes for predicting the prognosis of chronic obstructive pulmonary disease (COPD) do not use radiologic information and are ...
This study aimed to discuss the application value of the bias field correction algorithm in magnetic resonance imaging (MRI) images of patients with p...