Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care
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 …
The reporting of study and population characteristics in degenerative cervical myelopathy: A systematic review
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…