Using theoretical and modelling approaches, algorithms were implemented to automatically score children tests based on IMUs' data.
For the selected epitopes, a web-based tool, proteasomal cleavage/TAP transport/MHC class 1 combined predictor, 26 was also implemented to predict proteasomal cleavage score, TAP score, processing score, and MHC-1 binding score using SMM for each peptide.
An API has also been implemented to calculate the score distribution of a collection of interactions from a database.
A propensity score-matching model was implemented to take account of the selection bias due to observed individual heterogeneity.
First, a non-parametric frontier analysis is implemented to estimate efficiency scores, including a measure of technological innovation based on patent stocks.
A geometric distance-based machine learning scoring system was then implemented to derive a risk score from 0 to 100.
The scale can also be implemented to obtain a total score enabling comparison of the state of a patient over time.
Then, the time complexity of the algorithms we implemented to compute the hypergeometic score, the mutual information, odds ratio, and weighted support is O(D N M ).
The latter reached up to 85% when a clinical scoring system (McIsaac score) was implemented to enhance pretest probability [ 30].
Looking at the results of the probit model implemented to compute the propensity scores, we can verify that farms with a higher probability of being vertically coordinated are, on average, larger in size, adhering to certification schemes for products or processes, engaging prevalently salaried workers and they are more frequently managed by male and highly educated farmers.
