Subspace Clustering of Physiological Data From Acute Traumatic Brain Injury Patients: Retrospective Analysis Based on the PROTECT III Trial.
Sina EhsaniChandan K ReddyBrandon P ForemanJonathan RatcliffVignesh SubbianPublished in: JMIR biomedical engineering (2021)
Clustering approaches serve as an important step for phenotype definition and validation in clinical domains such as TBI, where patient and injury heterogeneity are among the major reasons for failure of clinical trials. The results from this study provide a foundation to develop scalable clustering algorithms for further research and validation.
Keyphrases
- traumatic brain injury
- single cell
- clinical trial
- rna seq
- end stage renal disease
- ejection fraction
- newly diagnosed
- machine learning
- liver failure
- chronic kidney disease
- phase ii
- deep learning
- prognostic factors
- study protocol
- case report
- randomized controlled trial
- electronic health record
- severe traumatic brain injury
- big data
- open label
- hepatitis b virus
- double blind