Venous thromboembolism (VTE) and major bleeding (MBE) are feared complications that are influenced by numerous host and surgical related factors. Using machine learning on contemporary data, our aim was to develop and validate a practical, easy-to-use al
It is worth noting that the time-on-task analysis was not performed for the KP, since this task was not self-paced. In the TSP, all instances had 20 cities and a time limit of 40 s. The number of cities and time limit were selected, based on pilot data, to ensure that the task...
Journal of Orthopaedic Surgery and Research volume 18, Article number: 673 (2023) Cite this article 1852 Accesses Metrics details Abstract Purpose Investigate the association between the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (...
Customer churn, when uncontrolled, is a serious problem for a business. To give you an idea about its impact on your business, let’s crunch some numbers. Say there are two companies that acquire the same number of customers per year and earn an average of $2000 per customer. But the c...
Biden in that of 2020. Singh et al. also proposed a method [29] based on sentiment analyses and machine learning on historical data to predict the number of seats that contesting parties were likely to win in the Punjab election of 2017. It can be seen that sentiment analysis is widely ...
was over-representation of carcinogens and of certain chemical classes in some of the databases, and that these databases consisted of a large number of old mammalian cell studies in which the criteria for positive or negative outcomes would most likely have been based on criteria no longer used...
However, the ability to conduct wide scale testing of patients has been limited by a number of factors including suitable resources for rt-PCR based testing for the presence of SARS-CoV-2. In addition, the standard test used has an 80% accuracy (compared to chest CT scan results) [5], ...
We used the randomForest package in R to fit the RF model. In the RF model training, we set the total number of variables in each decision tree as the default value in R. We set the candidate numbers of all decision trees in the RF model to 500, 1000, 1500 and 2000, and the num...
Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. By training a neural network, we developed a disease/mortality-specific proteomic risk score (ProRS) based on
A small number of observations showed unrealistically high numbers of clicks on the same tab in a very short period, which is likely a reflection of a student repeatedly clicking on a tab due to long loading time or other technical issues. To avoid oversampling these behaviors, we removed ...