The primary goal of surgical intervention for rectal cancer is to achieve an oncologic cure while preserving function. Since the introduction of total mesorectal excision (TME), the oncologic outcome has improved greatly in terms of local recurrence ...
Automatic sleep stage classification with cardiorespiratory signals has attracted increasing attention. In contrast to the traditional manual scoring based on polysomnography, these signals can be measured using advanced unobtrusive techniques that a...
Studies in health technology and informatics
27139378
Decision trees (DTs) are one of the most popular techniques for learning classification systems, especially when it comes to learning from discrete examples. In real world, many data occurred in a fuzzy form. Hence a DT must be able to deal with such...
BACKGROUND: Doctors mainly use scale tests and subjective judgment in the clinical diagnosis of depression. Researches have demonstrated that depression is associated with the dysfunction of the autonomic nervous system (ANS), where its modulation ca...
We present an experimental system of networks of coupled non-linear chemical reactors, which we theoretically model within a reaction-diffusion framework. The networks consist of patterned arrays of diffusively coupled nanoliter-scale reactors contai...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
30441611
Pain is usually measured by patient's self-report, which requires patient collaboration. Hence, the development of an objective automatic pain detection method would be useful in many clinical applications and patient populations. Previous studies ha...
KEY POINTS: Nausea is an adverse experience characterised by alterations in autonomic and cerebral function. Susceptibility to nausea is difficult to predict, but machine learning has yet to be applied to this field of study. The severity of nausea t...
Although self-report pain ratings are the gold standard in clinical pain assessment, they are inherently subjective in nature and significantly influenced by multidimensional contextual variables. Although objective biomarkers for pain could substant...
We utilized a data-driven, unsupervised machine learning approach to examine patterns of peripheral physiological responses during a motivated performance context across two large, independent data sets, each with multiple peripheral physiological me...