Table 1_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.xls by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Table 4_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.xls by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Supplementary file 1_Predicting first-time anaphylaxis in the elderly using stacked machine learning and population registers.docx by Toni Mora (8145624)

“…After applying chi-squared-based feature selection, we trained multiple classification algorithms—including logistic regression, decision trees, random forests, XGBoost, and a stacking ensemble. …”

Data Sheet 4_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.zip by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Table 2_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.xls by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Data Sheet 5_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.docx by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Data Sheet 1_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.zip by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Table 3_Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.xls by Jieqiong Tang (10362206)

“…This study aims to identify a marker related to neutrophil for the diagnosis and early progression of MI.</p>Methods<p>Key genes were screened using three machine learning algorithms to establish a diagnostic model. …”

Table 2_Use of artificial intelligence in predicting in-hospital cardiac and respiratory arrest in an acute care environment—implications for clinical practice.docx by Geerthy Thambiraj (22407274)

“…Background<p>Artificial intelligence (AI)-based models can augment clinical decision-making, including prediction, diagnosis, and treatment, in all aspects of medicine.…”

Table 1_Use of artificial intelligence in predicting in-hospital cardiac and respiratory arrest in an acute care environment—implications for clinical practice.docx by Geerthy Thambiraj (22407274)

“…Background<p>Artificial intelligence (AI)-based models can augment clinical decision-making, including prediction, diagnosis, and treatment, in all aspects of medicine.…”

Table 1_Real-world pharmacovigilance reports of hepatitis A inactivated and hepatitis B (recombinant) vaccine: insights from disproportionality analysis of the vaccine adverse even... by Yuhang Zhou (1391788)

“…The ROR and PRR algorithms have higher sensitivity but lower specificity. …”

Table 1_Ensemble machine learning for predicting renal function decline in chronic kidney disease: development and external validation.docx by Hong Chen (108084)

“…Clinical, demographic, and laboratory data were processed with rigorous quality control. …”

Data Sheet 1_Predicting axillary lymph node metastasis in breast cancer using a multimodal radiomics and deep learning model.docx by Fuyu Guo (4588312)

“…Objective<p>To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast cancer (BC). …”

Generating synthetic replicates of complex high-dimensional biological cell clusters by Mason Bradley (19850544)

“…Synthetic data offers superior analytical models with absolute accuracy, traceability, and reproducibility compared to current 'gold-standard' methods. The project uses synthetic cluster-generating benchmarking software often employed to assess clustering algorithms’ performances. …”

Table 2_Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target.xls by Hao Wu (65943)

“…</p>Methods<p>We leveraged gut microbiome data from 1,563 healthy individuals and 2,043 overweight patients sourced from the GMrepo database. …”

Table 1_Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target.xls by Hao Wu (65943)

“…</p>Methods<p>We leveraged gut microbiome data from 1,563 healthy individuals and 2,043 overweight patients sourced from the GMrepo database. …”

An ensemble machine learning framework with explainable artificial intelligence for predicting haemoglobin anaemia considering haematological markers by Dhruva Darshan B S (19964034)

“…The algorithms are further ensembled using a customized stacking approach. …”

Turkish_native_goat_genotypes by Yalçın YAMAN (20209833)

“…</p><p dir="ltr">Nine heterogeneous machine-learning models—including penalised linear methods, gradient-boosting algorithms, and interaction-sensitive tree ensembles—were applied to examine genotype–phenotype relationships. …”

Preprocessed GEFCom 2012 Wind Power Forecasting Dataset by Yuan Shi (22779782)

“…</p><p dir="ltr">This processed dataset is suitable for research and development in wind power forecasting models, offering a clean and standardized input for machine learning algorithms.…”

Supplementary file 2_Educators’ reflections on AI-automated feedback in higher education: a structured integrative review of potentials, pitfalls, and ethical dimensions.docx by Latifah Hamdan Alghamdi (22611518)

“…Research indicates that AI can enhance customization, deliver immediate feedback, optimize repetitive processes, and increase student engagement. Nonetheless, these advantages are persistently compromised by concerns regarding algorithmic bias, data privacy, the deterioration of teacher-student relationships, and inadequate professional growth. …”