The relevant code in the manuscript can be found in the supporting information data file. حسب Xini Fang (20861990)

Results of RF algorithm screening factors. حسب Jintao Li (448681)

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets حسب Haojie Wang (3072141)

"…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …"

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets حسب Haojie Wang (3072141)

"…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …"

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets حسب Haojie Wang (3072141)

"…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …"

Flow chart of the search process. حسب Lei Gao (6566)

Data Sheet 1_Association of microtubule-based processes gene expression with immune microenvironment and its predictive value for drug response in oestrogen receptor-positive breas... حسب Zhenfeng Huang (836949)

"…Prognostic risk models were developed via random forest, support vector machines and the least absolute shrinkage and selection operator algorithm. …"

Using artificial intelligence in the development of diagnostic models of coronary artery disease based on ECG features: A scoping review حسب Rong Yang (21661040)

"…</p><p dir="ltr">Extracted Fields:</p><table><tr><td><p dir="ltr">​​Category​​</p></td><td><p dir="ltr">​​Variables​​</p></td></tr><tr><td><p dir="ltr">Study Metadata​​</p></td><td><p dir="ltr">Authors, year, country, design, objectives</p></td></tr><tr><td><p dir="ltr">Population & Data Source​​</p></td><td><p dir="ltr">Cohort characteristics (age, sex), database (e.g., PTB-XL), sample size</p></td></tr><tr><td><p dir="ltr">AI Model Details​​</p></td><td><p dir="ltr">Algorithm (e.g., 1D-CNN, SVM), ECG features (e.g., QTc, spectral entropy)</p></td></tr><tr><td><p dir="ltr">Performance & Validation​​</p></td><td><p dir="ltr">Metrics (Acc, Sens, Spec), validation method (internal/external), generalizability</p></td></tr><tr><td><p dir="ltr">Critical Appraisal​​</p></td><td><p dir="ltr">Clinical relevance, limitations, implementation barriers</p></td></tr></table><p dir="ltr">7. …"

Machine learning-driven construction and validation of an intra-tumoral heterogeneity-associated prognostic model for bladder urothelial carcinoma حسب Yiwei Gu (11870279)

"…A 14-gene prognostic signature was developed using a combined LASSO and Random Survival Forest algorithm. …"

DATASET AI حسب Elena Stamate (18836305)

"…</li></ul><p dir="ltr">The dataset includes model-ready variables suitable for classification tasks and has been used to train and evaluate algorithms such as Extra Trees, Support Vector Machines (SVM), Random Forest, and Quadratic Discriminant Analysis (QDA). …"