AIMC Topic: Algorithms

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Cell type discrimination based on image features of molecular component distribution.

Scientific reports
Machine learning-based cell classifiers use cell images to automate cell-type discrimination, which is increasingly becoming beneficial in biological studies and biomedical applications. Brightfield or fluorescence images are generally employed as th...

Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age.

International journal of oral and maxillofacial surgery
This observational study aimed to use artificial intelligence to describe the impact of orthognathic treatment on facial attractiveness and age appearance. Pre- and post-treatment photographs (n=2164) of 146 consecutive orthognathic patients were col...

State representation learning for control: An overview.

Neural networks : the official journal of the International Neural Network Society
Representation learning algorithms are designed to learn abstract features that characterize data. State representation learning (SRL) focuses on a particular kind of representation learning where learned features are in low dimension, evolve through...

Fuzzy c-means-based architecture reduction of a probabilistic neural network.

Neural networks : the official journal of the International Neural Network Society
The efficiency of the probabilistic neural network (PNN) is very sensitive to the cardinality of a considered input data set. It results from the design of the network's pattern layer. In this layer, the neurons perform an activation on all input rec...

A New Approach on HCI Extracting Conscious Jaw Movements Based on EEG Signals Using Machine Learnings.

Journal of medical systems
Machine computer interfaces (MCI) are assistive technologies enabling paralyzed peoples to control and communicate their environments. This study aims to discover and represents a new approach on MCI using left/right motions of voluntary jaw movement...

A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning.

NeuroImage. Clinical
BACKGROUND AND PURPOSE: With extensive research efforts in place to address the clinical relevance of cerebral microbleeds (CMBs), there remains a need for fast and accurate methods to detect and quantify CMB burden. Although some computer-aided dete...

Prediction of 8-state protein secondary structures by a novel deep learning architecture.

BMC bioinformatics
BACKGROUND: Protein secondary structure can be regarded as an information bridge that links the primary sequence and tertiary structure. Accurate 8-state secondary structure prediction can significantly give more precise and high resolution on struct...

Evolving Spiking Neural Networks for online learning over drifting data streams.

Neural networks : the official journal of the International Neural Network Society
Nowadays huge volumes of data are produced in the form of fast streams, which are further affected by non-stationary phenomena. The resulting lack of stationarity in the distribution of the produced data calls for efficient and scalable algorithms fo...

Cross-Generation Kinship Verification with Sparse Discriminative Metric.

IEEE transactions on pattern analysis and machine intelligence
Kinship verification is a very important technique in many real-world applications, e.g., personal album organization, missing person investigation and forensic analysis. However, it is extremely difficult to verify a family pair with generation gap,...

Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.

Skeletal radiology
OBJECTIVE: Radiographic bone age assessment (BAA) is used in the evaluation of pediatric endocrine and metabolic disorders. We previously developed an automated artificial intelligence (AI) deep learning algorithm to perform BAA using convolutional n...