AIMC Topic: Neural Networks, Computer

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Scale-space approximated convolutional neural networks for retinal vessel segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Retinal fundus images are widely used to diagnose retinal diseases and can potentially be used for early diagnosis and prevention of chronic vascular diseases and diabetes. While various automatic retinal vessel segmentation...

Morphology-based classification of mycobacteria-infected macrophages with convolutional neural network: reveal EsxA-induced morphologic changes indistinguishable by naked eyes.

Translational research : the journal of laboratory and clinical medicine
EsxA is an essential virulence factor for Mycobacterium tuberculosis (Mtb) pathogenesis as well as an important biomarker for Mtb detection. In this study, we use light microscopy and deep learning-based image analysis to classify the morphologic cha...

Improved Deep Learning Network Based in combination with Cost-sensitive Learning for Early Detection of Ovarian Cancer in Color Ultrasound Detecting System.

Journal of medical systems
With the development of theories and technologies in medical imaging, most of the tumors can be detected in the early stage. However, the nature of ovarian cysts lacks accurate judgement, leading to that many patients with benign nodules still need F...

Determination of the physical domain for air quality monitoring stations using the ANP-OWA method in GIS.

Environmental monitoring and assessment
Air pollution is a major concern in some megacities of Iran. Specific cities in the country have reached an extremely harmful level of air pollution which poses a serious risk to the daily lives of Iranians. According to news reports, the air quality...

Outcome measurement in mental health services: insights from symptom networks.

BMC psychiatry
BACKGROUND: In mental health, outcomes are currently measured by changes of individual scores. However, such an analysis on individual scores does not take into account the interaction between symptoms, which could yield crucial information while inv...

Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2.

eNeuro
A crucial step in understanding visual input is its organization into meaningful components, in particular object contours and partially occluded background structures. This requires that all contours are assigned to either the foreground or the back...

Shunt connection: An intelligent skipping of contiguous blocks for optimizing MobileNet-V2.

Neural networks : the official journal of the International Neural Network Society
Enabling deep neural networks for tight resource constraint environments like mobile phones and cameras is the current need. The existing availability in the form of optimized architectures like Squeeze Net, MobileNet etc., are devised to serve the p...

Discrimination of EMG Signals Using a Neuromorphic Implementation of a Spiking Neural Network.

IEEE transactions on biomedical circuits and systems
An accurate description of muscular activity plays an important role in the clinical diagnosis and rehabilitation research. The electromyography (EMG) is the most used technique to make accurate descriptions of muscular activity. The EMG is associate...

Comparison of machine learning models for seizure prediction in hospitalized patients.

Annals of clinical and translational neurology
OBJECTIVE: To compare machine learning methods for predicting inpatient seizures risk and determine the feasibility of 1-h screening EEG to identify low-risk patients (<5% seizures risk in 48 h).