Table 4_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 1_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 6_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 3_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 9_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 7_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Table 2_Data-driven intelligent productivity prediction model for horizontal fracture stimulation.xlsx by Qian Li (114642)

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”

Personalized Dose Finding Using Outcome Weighted Learning by Guanhua Chen (1421857)

“…To estimate the optimal IDR using such data, we propose an outcome weighted learning method based on a nonconvex loss function, which can be solved efficiently using a difference of convex functions algorithm. …”

Fair Policy Targeting by Davide Viviano (14264992)

“…We adopt the nonmaleficence perspective of “first do no harm”: we select the fairest allocation <i>within</i> the Pareto frontier. We cast the optimization into a mixed-integer linear program formulation, which can be solved using off-the-shelf algorithms. …”

Image2_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image7_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Table1_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.XLSX by Shuo Wang (143908)

Image3_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image6_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image1_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image4_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Image5_A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data.JPEG by Shuo Wang (143908)

Data Sheet 1_A machine learning model for predicting the risk of diabetic nephropathy in individuals with type 2 diabetes mellitus.docx by Tingting Li (10553)

“…</p>Conclusions<p>The developed XGBoost model demonstrated optimal predictive accuracy for the occurrence of DKD in patients with T2DM. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…</i>, 2023</a>) (<a href="#sup1" target="_blank">Supplementary Data S2</a>). The final proposed betalain extraction procedure in the cape fig used 300 mg of frozen leaf samples ground with a mixer mill and homogenized with 0.5 mL of 50 % MeOH (aq.) and mixed for 20 min with a vortex. …”

DataSheet1_Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo.docx by Kaixian Yu (2836709)

“…A double filtering strategy was first used for discovering the overall skeleton of the target BN. To search for the optimal network structures we designed an adaptive SMC (adSMC) algorithm to increase the quality and diversity of sampled networks which were further improved by a third stage to reclaim edges missed in the skeleton discovery step. …”