The confidence change of the binary image after iteration. by Dingming Yang (8505990)

Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

Subjects:

ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

Subjects:

The accuracy score change matrix following model development. by Uğur Ejder (22683228)

Subjects:

The comparison of the accuracy score of the benchmark and the proposed models. by Uğur Ejder (22683228)

Subjects:

The prediction accuracy of simple versus hybrid models. by Uğur Ejder (22683228)

Subjects:

Flow diagram of the proposed model. by Uğur Ejder (22683228)

Subjects:

The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

Subjects:

Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). by Uğur Ejder (22683228)

Subjects:

The most effective active substances for subfertility treatment. by Uğur Ejder (22683228)

Subjects:

Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

Subjects:

The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)

Subjects:

Flow diagram of the conversion of drugs into active substances. by Uğur Ejder (22683228)

Subjects:

Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

Subjects:

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Segmentation, trace denoising and spike extraction framework. by Changjia Cai (10647521)

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... by Ramsés Noguez Imm (6658637)

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”