Litcius/Paper detail

Development of a multimodal machine-learning fusion model to non-invasively assess ileal Crohn’s disease endoscopic activity

Itai Guez, Gili Focht, Mary‐Louise C. Greer, Ruth Cytter-Kuint, Li‐tal Pratt, Denise Castro, Dan Turner, Anne M. Griffiths, Moti Freiman

2022Computer Methods and Programs in Biomedicine24 citationsDOI

Topics & Concepts

Receiver operating characteristicArtificial intelligenceCrohn's diseaseMagnetic resonance imagingWilcoxon signed-rank testMachine learningMedicineCorrelationLogistic regressionMean squared errorDiseaseComputer scienceMathematicsInternal medicineStatisticsRadiologyMann–Whitney U testGeometryInflammatory Bowel DiseaseGastrointestinal Bleeding Diagnosis and TreatmentColorectal Cancer Screening and Detection
Development of a multimodal machine-learning fusion model to non-invasively assess ileal Crohn’s disease endoscopic activity | Litcius