AIMC Topic: Pattern Recognition, Automated
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Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography.
Computer methods and programs in biomedicine
Jun 14, 2019
BACKGROUND AND OBJECTIVES: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical image analysis performance ...
Self-Paced Balance Learning for Clinical Skin Disease Recognition.
IEEE transactions on neural networks and learning systems
Jun 12, 2019
Class imbalance is a challenging problem in many classification tasks. It induces biased classification results for minority classes that contain less training samples than others. Most existing approaches aim to remedy the imbalanced number of insta...
An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.
Computer methods and programs in biomedicine
Jun 6, 2019
BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection and diagnosis of pulmonary diseases. A critical component in any computer-aided system, for either detection or diagnosis in digital CXR, is the auto...
Margin-Based Pareto Ensemble Pruning: An Ensemble Pruning Algorithm That Learns to Search Optimized Ensembles.
Computational intelligence and neuroscience
Jun 3, 2019
The ensemble pruning system is an effective machine learning framework that combines several learners as experts to classify a test set. Generally, ensemble pruning systems aim to define a region of competence based on the validation set to select th...
BACH: Grand challenge on breast cancer histology images.
Medical image analysis
May 31, 2019
Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysi...
Multi-Class Neural Networks to Predict Lung Cancer.
Journal of medical systems
May 31, 2019
Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of the patient records can help in diagnosing cancer during Stage 1. Usi...
Insights and approaches using deep learning to classify wildlife.
Scientific reports
May 31, 2019
The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the metho...
Machine learning identifies unaffected first-degree relatives with functional network patterns and cognitive impairment similar to those of schizophrenia patients.
Human brain mapping
May 30, 2019
Schizophrenia (SCZ) patients and their unaffected first-degree relatives (FDRs) share similar functional neuroanatomy. However, it remains largely unknown to what extent unaffected FDRs with functional neuroanatomy patterns similar to patients can be...
A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.
Journal of biophotonics
May 30, 2019
Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, au...
Gradually focused fine-grained sketch-based image retrieval.
PloS one
May 28, 2019
This paper focuses on fine-grained image retrieval based on sketches. Sketches capture detailed information, but their highly abstract nature makes visual comparisons with images more difficult. In spite of the fact that the existing models take into...
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