Estimation of the convergence of the algorithm for simulated ARGs of <i>L</i> leaves: VI distance to real MCCs as a function of the number of iterations of the SA optimization, scaled by <i>L</i>. by Pierre Barrat-Charlaix (9556592)

Proposed decision tree algorithm for thromboelastometry parameters to differentiate COVID-19 patients according to disease severity. by Rodrigo B. Aires (11949690)

Schematic of the iterative algorithm. by Pierre Barrat-Charlaix (9556592)

Image 4_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regression tree algorithm.pdf by Jun Gao (203098)

Subjects: “…classification and regression tree (CART) algorithm…”

Image 3_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regression tree algorithm.pdf by Jun Gao (203098)

Subjects: “…classification and regression tree (CART) algorithm…”

Image 2_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regression tree algorithm.pdf by Jun Gao (203098)

Subjects: “…classification and regression tree (CART) algorithm…”

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

Data_Sheet_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.PDF by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

An example of the algorithm of the ORFanID engine is explained in a UML flow chart diagram. by Richard S. Gunasekera (6752072)

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Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

The list of reactions and corresponding epidemiological events simulated by the Gillespie algorithm in our model, and the number of reactions in each category in function of the number of mutable sites <i>U</i>, number of susceptible individuals <i>T</i>, and the number of populations <i>K</i>. by Vladimir Shchur (5758916)

“…<p>The list of reactions and corresponding epidemiological events simulated by the Gillespie algorithm in our model, and the number of reactions in each category in function of the number of mutable sites <i>U</i>, number of susceptible individuals <i>T</i>, and the number of populations <i>K</i>.…”

ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

“…For the numerical case, user can directly provide <i>ab initio</i> data (adiabatic PESs and NACTs) as input files to this software or can generate those input files through in-built python codes interfacing MOLPRO followed by ADT calculation. …”

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

“…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”

Random Forest model with 1000 trees approximated the proposed algorithm on the same set of samples. by David L. Krongauz (15447260)

DESeq2 GFP vs <i>RNF43 WT</i>. by Alexis M. Thornton (11068403)

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Overall eVIP2 outputs for <i>ARAF</i> variants. by Alexis M. Thornton (11068403)

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Overall eVIP2 outputs for <i>RNF43</i> variants. by Alexis M. Thornton (11068403)

Subjects:

eVIP mutation-specific and WT-specific pathway analysis for LOF <i>RNF43 R117fs</i> and COF <i>RNF43 G659fs</i>. by Alexis M. Thornton (11068403)

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