AIMC Topic: Neural Networks, Computer

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An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images.

Computer methods and programs in biomedicine
OBJECTIVE: This paper presents a Radial Basis Functions Neural Network (RBFNN) based detection system, for automatic identification of Cerebral Vascular Accidents (CVA) through analysis of Computed Tomographic (CT) images.

DeepPap: Deep Convolutional Networks for Cervical Cell Classification.

IEEE journal of biomedical and health informatics
Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into "abnormal" and "normal" categories. However, the success of most trad...

Spotting L3 slice in CT scans using deep convolutional network and transfer learning.

Computers in biology and medicine
In this article, we present a complete automated system for spotting a particular slice in a complete 3D Computed Tomography exam (CT scan). Our approach does not require any assumptions on which part of the patient's body is covered by the scan. It ...

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

IEEE transactions on biomedical circuits and systems
We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework...

Deep Learning in Medical Imaging: General Overview.

Korean journal of radiology
The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient...

Pinning synchronization of memristor-based neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and ...

Modeling long-term human activeness using recurrent neural networks for biometric data.

BMC medical informatics and decision making
BACKGROUND: With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three ty...

Quad-phased data mining modeling for dementia diagnosis.

BMC medical informatics and decision making
BACKGROUND: The number of people with dementia is increasing along with people's ageing trend worldwide. Therefore, there are various researches to improve a dementia diagnosis process in the field of computer-aided diagnosis (CAD) technology. The mo...

Cascade recurring deep networks for audible range prediction.

BMC medical informatics and decision making
BACKGROUND: Hearing Aids amplify sounds at certain frequencies to help patients, who have hearing loss, to improve the quality of life. Variables affecting hearing improvement include the characteristics of the patients' hearing loss, the characteris...

A Deep Convolutional Neural Network-Based Framework for Automatic Fetal Facial Standard Plane Recognition.

IEEE journal of biomedical and health informatics
Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, conside...