Relevant data underlying the findings described in manuscript. حسب Lin Qi (128224)

Model-relevant variable data for external patients. حسب Lei Gao (6566)

الموضوعات:

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm حسب Pankaj Tyagi (20147683)

"…We first collected the dataset of 1278 odorant molecules with seven basic odor descriptors, and then 1875 physicochemical properties of odorant molecules were calculated. To obtain relevant physicochemical features, a feature reduction algorithm called PCA was also employed. …"

Classical Predictive Coding for motion processing. حسب Elnaz Nemati (21402730)

الموضوعات:

Effects of noise level and surround suppression threshold on model convergence time in the RDK task, experiment III. حسب Elnaz Nemati (21402730)

الموضوعات:

The relevant data file for this article. حسب Linsha Liu (20378293)

External cohort raw data. حسب Lei Gao (6566)

الموضوعات:

Internal cohort raw data. حسب Lei Gao (6566)

الموضوعات:

Data Sheet 1_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf حسب Habtamu Setegn Ngusie (12178327)

"…</p>Result<p>The prevalence of health facility delivery in East Africa was found to be 83.71%. The findings showed that the support vector machine (SVM) algorithm and CatBoost performed best in predicting the place of delivery, in which both of those algorithms scored an accuracy of 95% and an AUC of 0.98 after optimized with Bayesian optimization tuning and insignificant difference between them in all comprehensive analysis of metrics performance. …"

Data Sheet 2_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf حسب Habtamu Setegn Ngusie (12178327)

"…</p>Result<p>The prevalence of health facility delivery in East Africa was found to be 83.71%. The findings showed that the support vector machine (SVM) algorithm and CatBoost performed best in predicting the place of delivery, in which both of those algorithms scored an accuracy of 95% and an AUC of 0.98 after optimized with Bayesian optimization tuning and insignificant difference between them in all comprehensive analysis of metrics performance. …"

Echocardiographic and Clinical data comparison between None-BSH and BSH group patients in the Internal cohort. حسب Lei Gao (6566)

الموضوعات:

The GOR4 and SOPMA algorithm findings. حسب Ahmad Abdullah Mahdeen (19704401)

Relevant computed image data. حسب Zhaoyu Ku (20660546)

Summary of relevant works. حسب Bashir Olaniyi Sadiq (22478011)

Main code. حسب Jingguo Bi (21439766)

Key Findings and Methodologies. حسب Carlos M. Ardila (19996060)

Explanations when optimized towards prediction. حسب Bettina Soós (10860933)

الموضوعات:

The relevant code in the manuscript can be found in the supporting information data file. حسب Xini Fang (20861990)

CatBoost algorithm structure to predict clinical outcome. حسب Andrew McDonald (2307400)

الموضوعات: "…provide interpretable predictions…"

Data generation algorithm. حسب Aluwani Ramalata (21262977)