AIMC Topic: Neural Networks, Computer

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Biosignals learning and synthesis using deep neural networks.

Biomedical engineering online
BACKGROUND: Modeling physiological signals is a complex task both for understanding and synthesize biomedical signals. We propose a deep neural network model that learns and synthesizes biosignals, validated by the morphological equivalence of the or...

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem.

PLoS computational biology
There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiologic...

Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques, i.e., fuzzy-c-means clustering method (FCM), and the artificial neural network (ANN) and support vector machine (SVM), on an automated framework for ...

Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors.

IEEE transactions on biomedical circuits and systems
Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. The...

Risk Prediction for Portal Vein Thrombosis in Acute Pancreatitis Using Radial Basis Function.

Annals of vascular surgery
BACKGROUND: Acute pancreatitis (AP) can induce portosplenomesenteric vein thrombosis (PVT), which may generate higher morbidity and mortality. However current diagnostic modalities for PVT are still controversial. In recent decades, artificial neural...

Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features, which utilized specific characteristics of neural responses. A...

Stimulus-induced transitions between spike-wave discharges and spindles with the modulation of thalamic reticular nucleus.

Journal of computational neuroscience
It is believed that thalamic reticular nucleus (TRN) controls spindles and spike-wave discharges (SWD) in seizure or sleeping processes. The dynamical mechanisms of spatiotemporal evolutions between these two types of activity, however, are not well ...

Tracking-by-detection of surgical instruments in minimally invasive surgery via the convolutional neural network deep learning-based method.

Computer assisted surgery (Abingdon, England)
BACKGROUND: Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging...

Composite learning from adaptive backstepping neural network control.

Neural networks : the official journal of the International Neural Network Society
In existing neural network (NN) learning control methods, the trajectory of NN inputs must be recurrent to satisfy a stringent condition termed persistent excitation (PE) so that NN parameter convergence is obtainable. This paper focuses on command-f...

American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network.

Sensors (Basel, Switzerland)
This paper reports the design and analysis of an American Sign Language (ASL) alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication wi...