Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry.
Richard RiosRobert J. H. MillerNipun ManralTali SharirAndrew J. EinsteinMathews FishTerrence D. RuddyPhilipp A. KaufmannAlbert J. SinusasEdward J. MillerTimothy M. BatemanSharmila DorbalaMarcelo Di CarliSerge D. Van KriekingePaul KavanaghTejas ParekhJoanna X. LiangDamini DeyDaniel S. BermanPiotr J. SlomkaPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- patient specific
- missing values
- acute coronary syndrome
- machine learning
- missing data
- patient data
- blood flow
- data mining
- data imputation
- incomplete data
- therapy planning
- high dimensional data
- computational fluid dynamics
- cardiac cycle
- pattern recognition
- ct data
- image registration
- machine learning algorithms
- decision trees
- semi supervised
- knowledge discovery
- fully automatic
- image sequences
- model selection
- nearest neighbor
- support vector machine
- data analysis