<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = 2<i>ϖ</i> − 1. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = 2<i>ϖ</i> − 1 where . by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = 2<i>ϖ</i>. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = <i>ζ</i> = 2<i>ϖ</i>. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = 2<i>ϖ</i> − 1. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = <i>ζ</i> = 2<i>ϖ</i> − 1. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = 2<i>ϖ</i>. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = 2<i>ϖ</i> where . by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = 2<i>ϖ</i> where . by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = 2<i>ϖ</i> − 1. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = <i>ζ</i> = 2<i>ϖ</i>. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = 2<i>ϖ</i> − 1. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = 2<i>ϖ</i> − 1 where . by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> and <i>t</i> = 2<i>ϖ</i>. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

<i>R</i>_<i>v</i> for <i>n</i> = 2<i>ζ</i> + 1 and <i>t</i> = 2<i>ϖ</i>. by Kamran Azhar (20135873)

“…In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. …”

SHAP Values Distribution of Clinical Features. by Luyu Chai (12098204)

“…Multiple machine learning algorithms were evaluated, with model performance assessed through ROC curves, calibration curves, and precision-recall analysis. …”

ROC Curves Comparison of Machine Learning Models. by Luyu Chai (12098204)

“…Multiple machine learning algorithms were evaluated, with model performance assessed through ROC curves, calibration curves, and precision-recall analysis. …”

KS statistic plot in predicting LAT/SEC risk. by Chaoqun Huang (529718)

“…A retrospective study of 1,222 NVAF patients was conducted. Nine ML algorithms combined with demographic, clinical, and laboratory data were applied to develop prediction models for LAT/SEC in NVAF patients. …”

Multivariate logistic regression analysis. by Chaoqun Huang (529718)

“…A retrospective study of 1,222 NVAF patients was conducted. Nine ML algorithms combined with demographic, clinical, and laboratory data were applied to develop prediction models for LAT/SEC in NVAF patients. …”

Numerical heat transfer simulation by SPH. by Dan Fang (408648)

“…A numerical heat transfer simulation system is proposed based on the Lagrangian particle mathematical model and optimized numerical heat transfer simulation algorithm. …”