Table 5_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.docx حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Table 1_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.docx حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Table 4_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.docx حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Table 2_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.docx حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Image 3_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.tiff حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Image 2_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.tiff حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Image 4_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.tiff حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Image 1_Risk prediction model for precancerous gastric lesions based on magnifying endoscopy combined with narrow-band imaging features.tiff حسب Jingna Tao (20997176)

"…Receiver operating characteristic (ROC) curves were plotted using Python 3.12.4. Model accuracy, area under the ROC curve (AUC), sensitivity, and specificity were calculated for comprehensive validation.…"

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …"

Table 1_Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa.docx حسب Agmasie Damtew Walle (14716768)

"…A total weighted sample of 44,123 women was analyzed using Python version 3.11. Nine supervised machine-learning algorithms were applied, following Yufeng Guo's steps for supervised learning. …"

Hierarchical Deep Learning Framework for Automated Marine Vegetation and Fauna Analysis Using ROV Video Data حسب Bjørn Christian Weinbach (16918707)

"…</li><li>confidence: Confidence score for the prediction.</li><li>predicted_species: Predicted species label.…"

MLP_mod_application_v2.zip حسب Jian Li (20881226)

"…<p dir="ltr">The python source code for predicting the spatial location of macrophages using single cell dataset. …"