Mining multi-site clinical data to develop machine learning MRI biomarkers: application to neonatal hypoxic ischemic encephalopathy.
Rebecca J WeissSara V BatesYa'nan SongYue ZhangEmily M HerzbergYih-Chieh ChenMaryann GongIsabel ChienLily ZhangShawn N MurphyRandy L GollubPatricia Ellen GrantYangming OuPublished in: Journal of translational medicine (2019)
Within machine learning frameworks, we will test whether the quantified deviation from our recently-developed normative brain atlases can detect abnormal regions and predict outcomes for individual patients as accurately as, or even more accurately, than human experts. Trial Registration Not applicable. This study protocol mines existing clinical data thus does not meet the ICMJE definition of a clinical trial that requires registration.
Keyphrases
- machine learning
- study protocol
- clinical trial
- big data
- electronic health record
- randomized controlled trial
- end stage renal disease
- endothelial cells
- phase ii
- artificial intelligence
- ejection fraction
- open label
- magnetic resonance imaging
- phase iii
- newly diagnosed
- prognostic factors
- type diabetes
- resting state
- early onset
- adipose tissue
- double blind
- functional connectivity
- computed tomography
- insulin resistance
- brain injury
- subarachnoid hemorrhage
- multiple sclerosis