Article

Maximally informative feature selection using Information Imbalance: Application to COVID-19 severity prediction

2023-08-03

Abstract excerpt

<title>Abstract</title> <p>Clinical databases typically include, for each patient, many heterogeneous features, for example blood exams, the clinical history before the onset of the disease, the evolution of the symptoms, the results of imaging exams, and many others. We here propose to exploit a recently developed statistical approach, the Information Imbalance, to compare different subsets of patient features a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 03952f6e-5dc4-51ab-be4c-ed15480eb466
DOI: 10.21203/rs.3.rs-3184321/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Maximally informative feature selection using Information Imbalance: Application to COVID-19 severity predictionDOI 10.21203/rs.3.rs-3184321/v1Read

Development of an Accurate AI/ML-Driven COVID-19 Patient Stratification Model Predicting Disease Outcomes from Disproportionate and Scarce Clinical DatasetsSemantic proximity Read

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity typesSemantic proximity Read

Integrating AI/ML Models for Patient Stratification Leveraging Omics Dataset and Clinical Biomarkers from COVID-19 Patients: A Promising Approach to Personalized MedicineSemantic proximity Read

Integrating AI/ML Models for Patient Stratification Leveraging Omics Dataset and Clinical Biomarkers from COVID-19 Patients: A Promising Approach to Personalized MedicineSemantic proximity Read

Multicenter analysis of COVID-19 hospitalizations and stacking machine learning algorithms for prediction of high-risk patientsSemantic proximity Read

Machine learning uncovers blood test patterns subphenotypes at hospital admission discerning increased 30-day ICU mortality rates in COVID-19 elderly patientsSemantic proximity Read

Rapid assessment of COVID-19 mortality risk with GASS classifiersSemantic proximity Read

Sensitivity-Constrained Evolutionary Feature Selection for Imbalanced Medical Classification: A Case Study on Rotator Cuff Tear Surgery PredictionSemantic proximity Read

Data-Driven Inference of COVID-19 Clinical PrognosisSemantic proximity Read

Impact of Clinical and Genomic Factors on SARS-CoV2 Disease SeveritySemantic proximity Read

An Empirical study on the class imbalance handling techniques for different diseasesSemantic proximity Read

An Artificial Immune Network Combined with Improved SMOTE Oversampling Technique-Incorporated Robust Feature Selection Method for Imbalanced Medical DataSemantic proximity Read