AI Medical Compendium Topic:
Pattern Recognition, Automated

Clear Filters Showing 1001 to 1010 of 1642 articles

Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: False positive reduction is one of the most crucial components in an automated pulmonary nodule detection system, which plays an important role in lung cancer diagnosis and early treatment. The objective of this paper is to effectively add...

LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical ...

Hybrid Artificial Root Foraging Optimizer Based Multilevel Threshold for Image Segmentation.

Computational intelligence and neuroscience
This paper proposes a new plant-inspired optimization algorithm for multilevel threshold image segmentation, namely, hybrid artificial root foraging optimizer (HARFO), which essentially mimics the iterative root foraging behaviors. In this algorithm ...

Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets.

BioMed research international
In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detec...

Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means.

IEEE transactions on bio-medical engineering
OBJECTIVE: We introduce descriptor-based segmentation that extends existing patch-based methods by combining intensities, features, and location information. Since it is unclear which image features are best suited for patch selection, we perform a b...

Deep Neural Networks for Identifying Cough Sounds.

IEEE transactions on biomedical circuits and systems
In this paper, we consider two different approaches of using deep neural networks for cough detection. The cough detection task is cast as a visual recognition problem and as a sequence-to-sequence labeling problem. A convolutional neural network and...

Effects of adaptation on numerosity decoding in the human brain.

NeuroImage
Psychophysical studies have shown that numerosity is a sensory attribute susceptible to adaptation. Neuroimaging studies have reported that, at least for relatively low numbers, numerosity can be accurately discriminated in the intra-parietal sulcus....

When machine vision meets histology: A comparative evaluation of model architecture for classification of histology sections.

Medical image analysis
Classification of histology sections in large cohorts, in terms of distinct regions of microanatomy (e.g., stromal) and histopathology (e.g., tumor, necrosis), enables the quantification of tumor composition, and the construction of predictive models...

Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition.

Journal of biomedical semantics
BACKGROUND: Gene Ontology (GO) terms represent the standard for annotation and representation of molecular functions, biological processes and cellular compartments, but a large gap exists between the way concepts are represented in the ontology and ...