2023
Emergent Applications of Machine Learning for Diagnosing and Managing Appendicitis: A State-of-the-Art Review
Bhandarkar S, Tsutsumi A, Schneider E, Ong C, Paredes L, Brackett A, Ahuja V. Emergent Applications of Machine Learning for Diagnosing and Managing Appendicitis: A State-of-the-Art Review. Surgical Infections 2023, 25: 7-18. PMID: 38150507, DOI: 10.1089/sur.2023.201.Peer-Reviewed Original ResearchArtificial intelligence toolsNew artificial intelligence toolsArtificial neural networkSupport vector machineMachine learning-based toolLearning-based toolIntelligence toolsMachine learningUse casesNeural networkVector machineRandom forestAverage accuracyNovel solutionMachineEmergent applicationsAlgorithmOptimal modelQueriesHigh operator dependencyArt reviewAccuracyToolNetworkOperator dependency
2021
NIMG-67. A SYSTEMATIC REVIEW ON THE DEVELOPMENT OF MACHINE LEARNING MODELS FOR DIFFERENTIATING PCNSL FROM GLIOMAS
Petersen G, Shatalov J, Brim W, Subramanian H, cui J, Johnson M, Malhotra A, Aboian M, Brackett A. NIMG-67. A SYSTEMATIC REVIEW ON THE DEVELOPMENT OF MACHINE LEARNING MODELS FOR DIFFERENTIATING PCNSL FROM GLIOMAS. Neuro-Oncology 2021, 23: vi144-vi145. PMCID: PMC8598874, DOI: 10.1093/neuonc/noab196.565.Peer-Reviewed Original ResearchMachine learningDL algorithmsApplication of MLDeep learning algorithmsConvolutional neural networkMachine learning modelsSupport vector machineRisk of overfittingArtificial intelligenceLearning algorithmML algorithmsNeural networkVector machineLearning modelLarge datasetsNovel DLInternal datasetML methodsAlgorithmAverage AUCSearch strategyDatasetPromising resultsLearningRelated termsNIMG-71. IDENTIFYING CLINICALLY APPLICABLE MACHINE LEARNING ALGORITHMS FOR GLIOMA SEGMENTATION USING A SYSTEMATIC LITERATURE REVIEW
Tillmanns N, Lum A, Brim W, Subramanian H, Lin M, Bousabarah K, Malhotra A, cui J, Brackett A, Payabvash S, Ikuta I, Johnson M, Turowski B, Aboian M. NIMG-71. IDENTIFYING CLINICALLY APPLICABLE MACHINE LEARNING ALGORITHMS FOR GLIOMA SEGMENTATION USING A SYSTEMATIC LITERATURE REVIEW. Neuro-Oncology 2021, 23: vi145-vi145. PMCID: PMC8598815, DOI: 10.1093/neuonc/noab196.568.Peer-Reviewed Original ResearchConvolutional neural networkSegmentation of gliomasSupport vector machineGlioma segmentationDeep learningMachine learningLikelihood of overfittingMachine Learning AlgorithmsArtificial intelligenceLearning algorithmDice scoreML algorithmsTumor segmentationNeural networkVector machineCommon algorithmsSegmentationSame datasetML methodsTCIA datasetAlgorithmData acquisitionAccuracy reportingHigh accuracyLearning