Sort   by:  
 Page size 
ProteomicsPredicting the Protein Corona on Nanoparticles Using Random Forest Models with Nanoparticle, Protein, and Experimental Features
We describe the predicted composition and abundance of the protein corona as a function of protein, nanoparticle, and experimental features that serve as the input dataset in which our Random Forest Regression (RFR) and Random Forest Classifier (RFC) models were trained on. Predictions were made usi...
ORGANISM(S): Bos taurus (Bovine) 
2025-08-04 | PXD053700 | Pride
Random forest classifier Random forest regression Fetal bovine serum Nanoparticles Machine learning Protein corona Lc-ms/ms 
ProteomicsMulti-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer
Peripheral blood plasma was collected from unresectable stage III and IV non-small cell lung cancer patients who were negative for driver mutations before receiving immunotherapy. Then we classified samples according to the follow-up results after two courses of immunotherapy and non-targeted metabo...
ORGANISM(S): Homo Sapiens 
2024-12-18 | PXD058967 |
ModelsHuiyiLi2024 - Prediction of death risk in patients with acute diquat poisoning using Random Forest Model
The objective of this study was to develop and validate predictive models to assess the risk of death in patients with acute diquat (DQ) poisoning using innovative machine learning techniques. The study analyzed data from 201 consecutive patients admitted for deliberate oral intake of DQ between Feb...
2024-07-18 | MODEL2407180001 | BioModels
TranscriptomicsLncRNA profile study reveals a three-lncRNA signature associated with the survival of esophageal squamous cell carcinoma patients (independent set)
Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Des...
ORGANISM(S): Homo sapiens 
2014-03-07 | E-GEOD-53622 | biostudies-arrayexpress
TranscriptomicsLncRNA profile study reveals a three-lncRNA signature associated with the survival of esophageal squamous cell carcinoma patients (original)
Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Des...
ORGANISM(S): Homo sapiens 
2014-03-07 | E-GEOD-53624 | biostudies-arrayexpress
MetabolomicsPrediction and evaluation of the effect of pre-centrifugation sample management on the measurable untargeted LC-MS plasma metabolome

Optimal handling is the most important means to ensure adequate sample quality. We aimed to investigate whether pre-centrifugation delay time and temperature could be accurately predicted and to what extent variability induced by pre-centrifugation management can be adjusted for. We used untarget...

2021-10-13 | MTBLS2259 | MetaboLights
MetabolomicsDiscovery and validation of potential serum biomarkers for heart failure by untargeted metabolomics

Detection of biomarkers was extremely important for the early diagnosis, prognosis and therapy optimization of diseases. The purpose of this study was to investigate the differences in serum metabolites between patients with heart failure (HF) and healthy controls (HC), and to diagnose HF qualita...

2025-07-18 | MTBLS9586 | MetaboLights
UnknownA comparison of random forest variable selection methods for regression modeling of continuous outcomes.
Not available
S-EPMC11891652 | biostudies-literature
UnknownRandom forest regression for magnetic resonance image synthesis.
Not available
S-EPMC5099106 | biostudies-literature
UnknownSocioeconomic and environmental factors of poverty in China using geographically weighted random forest regression model.
Not available
S-EPMC8754530 | biostudies-literature
Sort   by:  
 Page size