0000000000372644

AUTHOR

Michael G. Fehlings

0000-0002-5722-6364

showing 2 related works from this author

Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care

2020

Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on “one-size-fits-all” guidelines. As epidemiological datasets continue to burgeon in size and complexity, powerful methods such as statistical machine learning and artificial intelligence (AI) become necessary to interpret and develop prognostic models from underlying data. Through such analysis, machine learning can be used to facilitate personalized medicine via its precise predictions. Additionally, other AI tools, such as natural language processing and computer vision, can play an instrumental part in personalizing the care provided to patients with …

Traumatic spinal cord injuryPrognosiPsychological interventionPatient characteristicsDiseaseSpinal cord injuryMachine learningcomputer.software_genreSpinal DiseaseMachine Learning03 medical and health sciences0302 clinical medicineArtificial IntelligenceHealth careFunctional StatuMedicineHumansSpine carePrecision MedicineDegenerative cervical myelopathyPrognostic modelsSpinal Cord InjuriesNatural Language ProcessingSpinal Cord Injuriebusiness.industryPrognosisPersonalized medicineFunctional Status030220 oncology & carcinogenesisSurgeryFunctional statusSpinal DiseasesNeurology (clinical)Personalized medicineArtificial intelligenceSpondylosisbusinesscomputerSpinal Cord Compression030217 neurology & neurosurgeryHuman
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The reporting of study and population characteristics in degenerative cervical myelopathy: A systematic review

2017

OBJECT: Degenerative cervical myelopathy [DCM] is a disabling and increasingly prevalent condition. Variable reporting in interventional trials of study design and sample characteristics limits the interpretation of pooled outcomes. This is pertinent in DCM where baseline characteristics are known to influence outcome. The present study aims to assess the reporting of the study design and baseline characteristics in DCM as the premise for the development of a standardised reporting set. METHODS: A systematic review of MEDLINE and EMBASE databases, registered with PROSPERO (CRD42015025497) was conducted in accordance with PRISMA guidelines. Full text articles in English, with >50 patients (p…

Systematic ReviewsImaging TechniquesPhysiologylcsh:MedicineSurgical and Invasive Medical ProceduresResearch and Analysis MethodsNervous SystemSpinal Cord DiseasesDiagnostic RadiologyUterine Cervical DiseasesDatabase and Informatics MethodsMathematical and Statistical TechniquesDiagnostic MedicineMedicine and Health SciencesPrevalenceHumansProspective StudiesDatabase SearchingStatistical Methodslcsh:ScienceRadiology and Imaginglcsh:RBiology and Life SciencesResearch AssessmentMagnetic Resonance ImagingElectrophysiologyNeuroanatomySpinal CordResearch DesignMultivariate AnalysisPhysical Scienceslcsh:QFemaleAnatomyMathematicsStatistics (Mathematics)Research ArticleNeurosciencePLoS ONE
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