Search results for "DNN"
showing 5 items of 5 documents
Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI
2020
In this paper, we present an evaluation of four encoder&ndash
Community detection-based deep neural network architectures: A fully automated framework based on Likert-scale data
2020
[EN] Deep neural networks (DNNs) have emerged as a state-of-the-art tool in very different research fields due to its adaptive power to the decision space since they do not presuppose any linear relationship between data. Some of the main disadvantages of these trending models are that the choice of the network underlying architecture profoundly influences the performance of the model and that the architecture design requires prior knowledge of the field of study. The use of questionnaires is hugely extended in social/behavioral sciences. The main contribution of this work is to automate the process of a DNN architecture design by using an agglomerative hierarchical algorithm that mimics th…
Deep Learning for Classifying Physical Activities from Accelerometer Data
2021
Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers’ methods to monitor a patient’s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify the physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the proposed models on two phy…
Heart rate variability in sick sinus syndrome: does it have a diagnostic role?
2019
BACKGROUND: Hypothesis of our study was that the irregular rhythm of sick sinus syndrome (SSS) was characterized by an augmented HRV. Objective was to assess whether SSS patients had a typical HRV profile. METHODS: We screened all 1947 consecutive Holter ECGs performed in our Units of Vascular Medicine and Internal Medicine and Cardioangiology at the University of Palermo (Italy) from April 2010 to September 2014. Among these, we selected 30 patients with ECG criteria of SSS. They were compared to 30 patients without SSS matched for age, sex and comorbidities. RESULTS: The SSS group had a lower mean heart rate (HR) (P=0.003), and a longer mean NN max-min longer (P<0.0005) compared to con…
A happiness degree predictor using the conceptual data structure for deep learning architectures
2017
Abstract Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventional methodologies are based on linear relationships, such as the commonly used Multivariate Linear Regression (MLR), which may suffer from the lack of representative capacity to the varied psychological features. Using Deep Neural Networks (DNN), we define a Happiness Degree Predictor (H-DP) based on the answers to five psychometric standardized questionnaires. Methods: A Data-Structure driven architecture for DNNs (D-SDNN) is proposed …