The world's population is aging: the expansion of the older adult population with multiple
physical and health issues is now a huge socio-economic concern worldwide. Among these …

Feature selection is playing an increasingly significant role with respect to many computer
vision applications spanning from object recognition to visual object tracking. However, most …

Emotion recognition still poses a challenge lying at the core of the rapidly growing area of
affective computing and is crucial for establishing a successful human–computer interaction …

Over the past two decades, several studies have paid great attention to biometric palmprint
recognition. Recently, most methods in literature adopted deep learning due to their high …

Feature selection is a necessary critical stage in data mining process. There is always an
arm race to build frameworks and libraries that ease and automate this process. In this …

Background: Cardiac resynchronization therapy (CRT) has significant nonresponse rates.
We assessed whether machine learning (ML) could predict CRT response beyond current …

Online streaming feature selection which deals with streaming features in an online manner
plays a critical role in big data problems. Many approaches have been proposed to handle …

The continuous monitoring of respiratory rate (RR) and oxygen saturation (SpO2) is crucial
for patients with cardiac, pulmonary, and surgical conditions. RR and SpO2 are used to …

Purpose To perform a radiomics analysis with comparisons of multidomain features and a
variety of feature selection strategies and classifiers, with the goal of evaluating the value of …

Purpose To identify optimal machine learning methods for radiomics-based differentiation of
local recurrence versus inflammation from post-treatment nasopharyngeal positron emission …