Topographical data analysis to identify high-density clusters in stroke patients undergoing post-acute rehabilitation.
Eliezer BoseLisa J WoodQing Mei WangPublished in: Topics in stroke rehabilitation (2020)
This study revealed that in addition to functional status on admission, stroke risk factors are associated with recovery outcomes. Future studies using TDA to analyze omic data, including clinical, biological, and sociodemographic factors, will accelerate the development of personalized treatment plans in post-acute stroke rehabilitation patients.
Keyphrases
- data analysis
- high density
- risk factors
- patients undergoing
- end stage renal disease
- atrial fibrillation
- chronic kidney disease
- newly diagnosed
- emergency department
- liver failure
- prognostic factors
- type diabetes
- machine learning
- single cell
- health insurance
- adipose tissue
- case control
- deep learning
- replacement therapy
- blood brain barrier
- subarachnoid hemorrhage
- patient reported
- smoking cessation