Performance confidence intervals. by Nicola Lazzarini (3528197)

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Baseline characteristics of patients in the study cohort. by Nicola Lazzarini (3528197)

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Input features. by Nicola Lazzarini (3528197)

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Most important predictive features. by Nicola Lazzarini (3528197)

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Age feature importance. by Nicola Lazzarini (3528197)

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Machine learning vs. clinicians. by Nicola Lazzarini (3528197)

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ROC curves. by Nicola Lazzarini (3528197)

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PR curves. by Nicola Lazzarini (3528197)

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Overview of the cohort definition process. by Nicola Lazzarini (3528197)

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Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx by Lian Li (49049)

“…Objective<p>This study utilizes real-world data from primary membranous nephropathy (PMN) patients to preliminarily develop a venous thromboembolism (VTE) risk prediction model with machine learning. …”

The baseline case–the model in the absence of sentinel plants. by Francesca A. Lovell-Read (14378253)

The prediction error of each model. by Hao Yang (328526)

“…This study proposes an explainable deep learning framework, the Improved Kepler Optimization Algorithm-Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (IKOA-CNN-BiGRU-Attention) model, for precise debris flow hazard prediction in the Yunnan section of the Nujiang River Basin, China. …”

Results for model hyperparameter values. by Hao Yang (328526)

“…This study proposes an explainable deep learning framework, the Improved Kepler Optimization Algorithm-Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (IKOA-CNN-BiGRU-Attention) model, for precise debris flow hazard prediction in the Yunnan section of the Nujiang River Basin, China. …”

Stability analysis of each model. by Hao Yang (328526)

“…This study proposes an explainable deep learning framework, the Improved Kepler Optimization Algorithm-Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (IKOA-CNN-BiGRU-Attention) model, for precise debris flow hazard prediction in the Yunnan section of the Nujiang River Basin, China. …”

Robustness Analysis of each model. by Hao Yang (328526)

“…This study proposes an explainable deep learning framework, the Improved Kepler Optimization Algorithm-Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (IKOA-CNN-BiGRU-Attention) model, for precise debris flow hazard prediction in the Yunnan section of the Nujiang River Basin, China. …”

Multivariable Cox proportional hazard model^b'*' for the composite outcome among the post-propensity matched COVID-19 infected patients in the Banner Healthcare System be... by Srilekha Sridhara (15374444)

Table_1_Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.docx by Jiajin He (13386702)

Table_1_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.XLSX by Qin-Yu Zhao (10014626)

Table_2_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.DOCX by Qin-Yu Zhao (10014626)

Table_1_Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.docx by Jiang Zhu (40858)