A systematic review of ionizing radiation-induced glaucoma: clinical manifestations, pathogenesis, and current treatment approaches by Anqi Wu (3413069)

“…Advancing the field will require mechanistic studies to clarify radiation-induced optic neuropathy and vascular injury, alongside well-designed trials to establish preventive strategies and evidence-based treatment algorithms.</p>…”

Supplementary Material for: Questionnaire survey on the current status of advanced therapy for inflammatory bowel disease in Asia by figshare admin karger (2628495)

“…Region-specific evidence-based algorithms for selecting advanced therapies for IBD should be established.…”

Data Sheet 1_Accurate informatic modeling of tooth enamel pellicle interactions by training substitution matrices with Mat4Pep.doc by Jeremy Horst Keeper (20458274)

“…Sampling diverse matrices, adding biological control sequences, and optimizing matrix refinement algorithms improve discrimination from 0.81 to 0.99 AUC in leave-one-out experiments. …”

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. …”

Image 1_Identification of routine blood derived hematological and lipid indices in ILD through machine learning; a retrospective case-control study.tif by Lichen Zhu (22399222)

“…Future studies will focus on further optimizing the model and validating it in larger multicenter cohorts.…”

Table 1_Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest.... by Qiang Wu (31071)

“…Objective<p>In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP.…”

Table 1_High-resolution vessel wall imaging-driven radiomic analysis for the precision prediction of intracranial aneurysm rupture risk: a promising approach.docx by Wenqing Yuan (10896337)

“…Univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were performed on the training cohort features to identify optimal rupture-associated features. The Rad-score model was constructed by calculating the total score derived from the weighted sum of optimal radiomic features, and three ML models were built using the XGBoost, LightGBM, and CART algorithms, and evaluated using both the test and external validation cohorts.…”

Data Sheet 1_Construction of a diagnostic model for temporal lobe epilepsy using interpretable deep learning: disease-associated markers identification.docx by Tianyu Wang (397547)

“…</p>Results<p>After comparative analysis, a Deep Neural Network (DNN) model with 10 optimized genetic features achieved perfect diagnostic performance (AUC = 1.000, accuracy = 1.000). …”

Table 2_Hemophagocytic lymphohistiocytosis as the initial manifestation of Epstein–Barr virus-related T/NK-cell lymphoproliferative disorders in a pediatric patient: a case report... by Lianwei Ma (10517346)

“…This case highlights that when EBV infection triggers a series of complex EBV-T/NK-LPDs occurring sequentially or simultaneously, the differential diagnosis and treatment become difficult, which can easily lead to delays in diagnosis and treatment. Developing optimized diagnostic algorithms and evidence-based treatment strategies is essential to improve outcomes of patients.…”

Supplementary file 1_Hemophagocytic lymphohistiocytosis as the initial manifestation of Epstein–Barr virus-related T/NK-cell lymphoproliferative disorders in a pediatric patient: a... by Lianwei Ma (10517346)

“…This case highlights that when EBV infection triggers a series of complex EBV-T/NK-LPDs occurring sequentially or simultaneously, the differential diagnosis and treatment become difficult, which can easily lead to delays in diagnosis and treatment. Developing optimized diagnostic algorithms and evidence-based treatment strategies is essential to improve outcomes of patients.…”

Table 4_Hemophagocytic lymphohistiocytosis as the initial manifestation of Epstein–Barr virus-related T/NK-cell lymphoproliferative disorders in a pediatric patient: a case report... by Lianwei Ma (10517346)

“…This case highlights that when EBV infection triggers a series of complex EBV-T/NK-LPDs occurring sequentially or simultaneously, the differential diagnosis and treatment become difficult, which can easily lead to delays in diagnosis and treatment. Developing optimized diagnostic algorithms and evidence-based treatment strategies is essential to improve outcomes of patients.…”

Table 3_Hemophagocytic lymphohistiocytosis as the initial manifestation of Epstein–Barr virus-related T/NK-cell lymphoproliferative disorders in a pediatric patient: a case report... by Lianwei Ma (10517346)

“…This case highlights that when EBV infection triggers a series of complex EBV-T/NK-LPDs occurring sequentially or simultaneously, the differential diagnosis and treatment become difficult, which can easily lead to delays in diagnosis and treatment. Developing optimized diagnostic algorithms and evidence-based treatment strategies is essential to improve outcomes of patients.…”

Table 1_Hemophagocytic lymphohistiocytosis as the initial manifestation of Epstein–Barr virus-related T/NK-cell lymphoproliferative disorders in a pediatric patient: a case report... by Lianwei Ma (10517346)

“…This case highlights that when EBV infection triggers a series of complex EBV-T/NK-LPDs occurring sequentially or simultaneously, the differential diagnosis and treatment become difficult, which can easily lead to delays in diagnosis and treatment. Developing optimized diagnostic algorithms and evidence-based treatment strategies is essential to improve outcomes of patients.…”

2000–2020 Monthly Air Quality Index (AQI) Dataset of China by Chaohao Ling (19840471)

“…., 2-m air temperature, 10-m wind speed from the China Meteorological Forcing Dataset), vegetation metrics (Normalized Difference Vegetation Index [NDVI], Net Primary Productivity [NPP]), anthropogenic factors (downscaled GDP, population density, Human Footprint Index), and soil properties (pH, soil organic carbon from China’s High-Resolution National Soil Information Grid). Four tree-based ensemble algorithms (Random Forest [RF], Gradient Boosting Machine [GBM], CatBoost, XGBoost) were compared, with the RF model selected as optimal (test set: R² = 0.83, Root Mean Square Error [RMSE] = 10.25, Mean Absolute Error [MAE] = 9.03) after validation via 10-fold geographic stratified cross-validation and 100 bootstrap iterations; Recursive Feature Elimination (RFE) further refined 14 core predictors to minimize overfitting. …”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”

Multispectral UAV imagery and machine learning for morphological differentiation of two tropical C4-forage grasses in an integrated crop-livestock system in the State of Goias, Bra... by Diogo Castilho Silva (15353644)

“…Three machine learning algorithms (Random Forest – RF, SVM, XGBoost) were compared using 200,000 annotated pixels. …”

Data Sheet 1_Early prediction of sepsis-induced coagulopathy in the ICU using interpretable machine learning: a multi-center retrospective cohort study.docx by Tao Sha (18829884)

“…Finally, the best-performing model was implemented as a web-based Shiny application featuring an interactive interface.…”

Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca (20435036)

“…Machine learning algorithms have been applied to perform seagrass detection, obtaining a seagrass cartography up to 30 m of depth, estimating 505.6 km² of seagrass habitat extent. …”

Image 2_Development and application of machine learning models for hematological disease diagnosis using routine laboratory parameters: a user-friendly diagnostic platform.jpeg by Jingya Liu (13338460)

“…</p>Methods<p>In this study, we employed 54 clinical and conventional laboratory parameters. By optimally combining multiple feature selection methods and machine learning algorithms, we developed 7 machine learning models with varying feature set sizes. …”

Data Sheet 1_Development and application of machine learning models for hematological disease diagnosis using routine laboratory parameters: a user-friendly diagnostic platform.doc... by Jingya Liu (13338460)

“…</p>Methods<p>In this study, we employed 54 clinical and conventional laboratory parameters. By optimally combining multiple feature selection methods and machine learning algorithms, we developed 7 machine learning models with varying feature set sizes. …”