ResNeXt101 training and results. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Architecture of ConvNet. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Comparison of state-of-the-art method. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Proposed ResNeXt101 operational flow. حسب Subathra Gunasekaran (19492680)

"…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …"

Data_Sheet_1_Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived paramete... حسب Kuo-Yang Huang (4470730)

Internal architecture of the SPAM-XAI model. حسب Mohd Mustaqeem (19106494)

"…However, SDP faces challenges like imbalanced data, high-dimensional features, model overfitting, and outliers. …"

Data_Sheet_1_Degenerate Beta autoregressive model for proportion time-series with zeros or ones: An application to antimicrobial resistance rate using R shiny app.PDF حسب Jevitha Lobo (14368401)

Data_Sheet_1_Degenerate Beta autoregressive model for proportion time-series with zeros or ones: An application to antimicrobial resistance rate using R shiny app.PDF حسب Jevitha Lobo (14368401)

Image 2_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png حسب Min Liang (363007)

"…</p>Conclusions<p>This study presents a robust machine learning model and a web-based tool that assist healthcare practitioners in personalized clinical decision-making and treatment optimization for ASC patients following primary tumor resection.…"

Image 1_Integrative prognostic modeling for stage III lung adenosquamous carcinoma post-tumor resection: machine learning insights and web-based implementation.png حسب Min Liang (363007)

"…</p>Conclusions<p>This study presents a robust machine learning model and a web-based tool that assist healthcare practitioners in personalized clinical decision-making and treatment optimization for ASC patients following primary tumor resection.…"

Data_Sheet_1_Comparison of Radiomics-Based Machine-Learning Classifiers in Diagnosis of Glioblastoma From Primary Central Nervous System Lymphoma.PDF حسب Chaoyue Chen (7298480)

Overview of SPAM-XAI model complete architecture. حسب Mohd Mustaqeem (19106494)

"…However, SDP faces challenges like imbalanced data, high-dimensional features, model overfitting, and outliers. …"

Data_Sheet_1_Risk factors of lymph node metastasis or lymphovascular invasion for superficial esophageal squamous cell carcinoma: A practical and effective predictive nomogram base... حسب Yali Tao (10772160)

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"

Big Data Model Building Using Dimension Reduction and Sample Selection حسب Lih-Yuan Deng (17081779)

"…The proposed subdata can retain most characteristics of the original big data. It is also more robust that one can fit various response model and select the optimal model. …"

Data_Sheet_1_A Machine-Learning Approach for Dynamic Prediction of Sepsis-Induced Coagulopathy in Critically Ill Patients With Sepsis.docx حسب Qin-Yu Zhao (10014626)

Data_Sheet_2_A Machine-Learning Approach for Dynamic Prediction of Sepsis-Induced Coagulopathy in Critically Ill Patients With Sepsis.xlsx حسب Qin-Yu Zhao (10014626)

Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis حسب Qing Hu (152962)

"…Machine learning analysis revealed significant influences of catalyst type, catalyst concentration, and the ratio of aldehyde-to-ketone on reaction efficiency. A kinetic model was established by focusing on two primary reactions: Cy = O oxidation (Reaction I) and PRA auto-oxidation (Reaction II), from which the reliable kinetic parameters were obtained via genetic algorithm-based optimization. …"

Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis حسب Qing Hu (152962)

"…Machine learning analysis revealed significant influences of catalyst type, catalyst concentration, and the ratio of aldehyde-to-ketone on reaction efficiency. A kinetic model was established by focusing on two primary reactions: Cy = O oxidation (Reaction I) and PRA auto-oxidation (Reaction II), from which the reliable kinetic parameters were obtained via genetic algorithm-based optimization. …"

S1 Code - حسب Gaosha Li (20570760)

"…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …"