Two-Stage Prediction of Comorbid Cancer Patient Survivability Based on Improved Infinite Feature Selection
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DOI: 10.1109/access.2020.3016998
Abstract: The modeling of comorbid cancer patients’ survivability has theoretical significance and practical needs. Cancer survivability prediction may provide guidance for clinical decision making and personalized medicine. The Surveillance, Epidemiology, and End Results(SEER) program provides large… read more here.
Keywords: feature selection; cancer; comorbid cancer; prediction ... See more keywords
Infinite Feature Selection Based Arrhythmia Classification Using Semantic Features and Random Forest
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DOI: 10.22266/ijies2019.0630.21
Abstract: In this research study, arrhythmia classification was assessed by using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. After signal acquisition, semantic feature extraction (combination of statistical, entropy, linear and non-linear features) was used… read more here.
Keywords: arrhythmia classification; methodology; feature selection; feature ... See more keywords