Comparison of ranks for classification algorithms across performance metrics. by Stephen R. Piccolo (8367780)

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif by Xuehui Fan (10762662)

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

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

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

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

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

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

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

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

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

Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”

DataSheet1_Towards Computational Modeling of Human Goal Recognition.pdf by Shify Treger (11973125)

“…Moreover, the proposed algorithm marries rationality-based and plan-library based methods seamlessly.…”

DataSheet1_Towards Computational Modeling of Human Goal Recognition.pdf by Shify Treger (11973125)

“…Moreover, the proposed algorithm marries rationality-based and plan-library based methods seamlessly.…”

Table 1_Advances in the application of human-machine collaboration in healthcare: insights from China.docx by Wuzhen Wang (20675405)

“…“Human–machine collaboration” is based on an intelligent algorithmic system that utilizes the complementary strengths of humans and machines for data exchange, task allocation, decision making and collaborative work to provide more decision support. …”

Aluminum alloy industrial materials defect by Ying Han (20349093)

“…</p><h2>Description of the data and file structure</h2><p dir="ltr">This is a project based on the YOLOv8 enhanced algorithm for aluminum defect classification and detection tasks.…”