2022
Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment
Petersen G, Shatalov J, Verma T, Brim WR, Subramanian H, Brackett A, Bahar RC, Merkaj S, Zeevi T, Staib LH, Cui J, Omuro A, Bronen RA, Malhotra A, Aboian MS. Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment. American Journal Of Neuroradiology 2022, 43: 526-533. PMID: 35361577, PMCID: PMC8993193, DOI: 10.3174/ajnr.a7473.Peer-Reviewed Original ResearchMeSH KeywordsGliomaHumansLymphomaMachine LearningMagnetic Resonance ImagingReproducibility of ResultsConceptsMachine learning-based methodsLearning-based methodsBalanced data setData setsVector machine modelMachine learningClassification algorithmsMachine modelMachineAlgorithmData basesPrediction modelPromising resultsPrimary CNS lymphomaPrediction model study RiskRisk of biasRadiomic featuresClassifierSetCNS lymphomaWebLearningFeaturesQualitySystematic reviewEnsuring rigor in systematic reviews: Part 7, critical appraisal of systematic review quality
Brackett A, Batten J. Ensuring rigor in systematic reviews: Part 7, critical appraisal of systematic review quality. Heart & Lung 2022, 53: 32-35. PMID: 35124337, DOI: 10.1016/j.hrtlng.2022.01.008.Peer-Reviewed Original Research
2020
Ensuring the rigor in systematic reviews: Part 4, screening the results
Brackett A, Batten J. Ensuring the rigor in systematic reviews: Part 4, screening the results. Heart & Lung 2020, 50: 182-184. PMID: 33249388, DOI: 10.1016/j.hrtlng.2020.11.002.Peer-Reviewed Original Research