Exposomic Signatures of Cervical Pain.
Carlos J MaldonadoJessica A White-PhillipYuliang LiuY Sammy ChoiPublished in: Military medicine (2023)
Our longitudinal exposomic signatures-based approach aims to complement the outcomes of data science and analytics from Medical Assessment and Readiness System with validations of objective biochemical indicator species observed in Army and Marine Aviation community members suffering from CP. This initial approach using parallel track complementarity has the potential of substantiating the underlying mechanisms foundational to design prospective personalized algorithms that can be used as a predictive model. Finally, a specific evaluation of occupational risk factors may provide insight into factors not readily ascertained from the civilian literature.
Keyphrases
- risk factors
- big data
- machine learning
- healthcare
- genome wide
- chronic pain
- systematic review
- public health
- pain management
- mental health
- electronic health record
- deep learning
- artificial intelligence
- neuropathic pain
- cross sectional
- human health
- metabolic syndrome
- type diabetes
- risk assessment
- adipose tissue
- spinal cord
- glycemic control