2024
Deep learning for prediction of post-thrombectomy outcomes based on admission CT angiography in large vessel occlusion stroke
Sommer J, Dierksen F, Zeevi T, Tran A, Avery E, Mak A, Malhotra A, Matouk C, Falcone G, Torres-Lopez V, Aneja S, Duncan J, Sansing L, Sheth K, Payabvash S. Deep learning for prediction of post-thrombectomy outcomes based on admission CT angiography in large vessel occlusion stroke. Frontiers In Artificial Intelligence 2024, 7: 1369702. PMID: 39149161, PMCID: PMC11324606, DOI: 10.3389/frai.2024.1369702.Peer-Reviewed Original ResearchEnd-to-endComputed tomography angiographyLarge vessel occlusionConvolutional neural networkDeep learning pipelineTrain separate modelsLogistic regression modelsResNet-50Deep learningAdmission computed tomography angiographyNeural networkLearning pipelineAdmission CT angiographyPreprocessing stepDiagnosis of large vessel occlusionsLarge vessel occlusion strokeReceiver operating characteristic areaEnsemble modelAutomated modelPre-existing morbidityCT angiographyReperfusion successNeurological examCross-validationOcclusion stroke
2021
NIMG-23. MACHINE LEARNING METHODS IN GLIOMA GRADE PREDICTION: A SYSTEMATIC REVIEW
Bahar R, Merkaj S, Brim W, Subramanian H, Zeevi T, Kazarian E, Lin M, Bousabarah K, Payabvash S, Ivanidze J, Cui J, Tocino I, Malhotra A, Aboian M. NIMG-23. MACHINE LEARNING METHODS IN GLIOMA GRADE PREDICTION: A SYSTEMATIC REVIEW. Neuro-Oncology 2021, 23: vi133-vi133. PMCID: PMC8598529, DOI: 10.1093/neuonc/noab196.523.Peer-Reviewed Original ResearchClassical machine learningConvolutional neural networkDeep learningSupport vector machineMachine learningMachine learning technologiesHigher grading accuracyMachine learning methodsArtificial intelligenceML applicationsHighest performing modelLearning technologyNeural networkMultimodal sequencesLearning methodsVector machineCommon algorithmsML methodsTCIA datasetPrimary machinePrediction accuracyGrade predictionGrading accuracyMachinePerforming modelNIMG-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
2018
Pretreatment Identification of Head and Neck Cancer Nodal Metastasis and Extranodal Extension Using Deep Learning Neural Networks
Kann BH, Aneja S, Loganadane GV, Kelly JR, Smith SM, Decker RH, Yu JB, Park HS, Yarbrough WG, Malhotra A, Burtness BA, Husain ZA. Pretreatment Identification of Head and Neck Cancer Nodal Metastasis and Extranodal Extension Using Deep Learning Neural Networks. Scientific Reports 2018, 8: 14036. PMID: 30232350, PMCID: PMC6145900, DOI: 10.1038/s41598-018-32441-y.Peer-Reviewed Original ResearchConceptsExtranodal extensionNodal metastasisPatient managementNeck cancer patient managementBlinded test setClinical decision-making toolCancer patient managementNeck cancer managementPostoperative pathologyPretreatment identificationCancer managementMetastasisRadiographic identificationCharacteristic curveCliniciansConvolutional neural networkHuman cliniciansNeural networkHeadDeep learning convolutional neural networkLymphDeep learning neural network