A deep learning approach to detect sleep stages
نویسندگان
چکیده
منابع مشابه
A Machine Learning Approach to Classify Sleep Stages of Rats
Identifying the vigilance states of the mammalian is an important research topic to bioscience in recently years, which the vigilance states is usually categorized as slow wave sleep, rapid eye movement sleep, and awake, etc. To discriminate difference vigilance states, a well-trained expert needs spend a long time to analyze a mass of physiological record data. In this paper, we proposed an au...
متن کاملA Deep Learning Approach to Detect SNP Interactions
The susceptibility of complex diseases are characterised by numerous genetic, lifestyle, and environmental causes individually or due to their interaction effects. The recent explosion in detecting genetic interacting factors is increasingly revealing the underlying biological networks behind complex diseases. Several computational methods are explored to discover interacting polymorphisms amon...
متن کاملLearning to Detect Red Lesions in Fundus Photographs: An Ensemble Approach based on Deep Learning
Diabetic retinopathy (DR) is one of the leading causes of preventable blindness in the world. Its earliest sign are red lesions, a general term that groups both microaneurysms (MAs) and hemorrhages (HEs). In daily clinical practice, these lesions are manually detected by physicians using fundus photographs. However, this task is tedious and time consuming, and requires an intensive effort due t...
متن کاملA Deep Learning Approach to Machine Transliteration
In this paper we present a novel transliteration technique which is based on deep belief networks. Common approaches use finite state machines or other methods similar to conventional machine translation. Instead of using conventional NLP techniques, the approach presented here builds on deep belief networks, a technique which was shown to work well for other machine learning problems. We show ...
متن کاملA Deep Learning Approach to Identify Diabetes
The primary objective of this paper is to predict onset of using deep learning and also as to predict the risk factor and severity of diabetics. The methods are implemented on in a conditional data set of diabetes. The model involves deep learning, in the form of a deep neural network through which we are able to apply predictive analytics on said diabetes data set and obtain optimal results. A...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2020
ISSN: 1877-0509
DOI: 10.1016/j.procs.2020.09.280