AIMC Topic: Algorithms

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Nodule Localization in Thyroid Ultrasound Images with a Joint-Training Convolutional Neural Network.

Journal of digital imaging
The accurate localization of nodules in ultrasound images can convey crucial information to support a reliable diagnosis. However, this is usually challenging due to low contrast and image artifacts, especially in thyroid ultrasound images where nodu...

Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker.

Cerebral cortex (New York, N.Y. : 1991)
The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing in...

[From external assessment of pain to automated multimodal measurement of pain intensity : Narrative review of state of research and clinical perspectives].

Schmerz (Berlin, Germany)
BACKGROUND: In patients with limited communication skills, the use of conventional scales or external assessment is only possible to a limited extent or not at all. Multimodal pain recognition based on artificial intelligence (AI) algorithms could be...

A Systematic Evaluation of Interneuron Morphology Representations for Cell Type Discrimination.

Neuroinformatics
Quantitative analysis of neuronal morphologies usually begins with choosing a particular feature representation in order to make individual morphologies amenable to standard statistics tools and machine learning algorithms. Many different feature rep...

[Multimodal recognition of pain intensity and pain modality with machine learning].

Schmerz (Berlin, Germany)
BACKGROUND: The objective recording of subjectively experienced pain is a problem that has not been sufficiently solved to date. In recent years, data sets have been created to train artificial intelligence algorithms to recognize patterns of pain in...

Improved 3D tracking and automated classification of rodents' behavioral activity using depth-sensing cameras.

Behavior research methods
Analysis of rodents' behavior/activity is of fundamental importance in many research fields. However, many behavioral experiments still rely on manual scoring, with obvious problems in reproducibility. Despite important advances in video-analysis sys...

Predicting bacterial virulence factors - evaluation of machine learning and negative data strategies.

Briefings in bioinformatics
Bacterial proteins dubbed virulence factors (VFs) are a highly diverse group of sequences, whose only obvious commonality is the very property of being, more or less directly, involved in virulence. It is therefore tempting to speculate whether their...

Convolutional neural network-based annotation of bacterial type IV secretion system effectors with enhanced accuracy and reduced false discovery.

Briefings in bioinformatics
The type IV bacterial secretion system (SS) is reported to be one of the most ubiquitous SSs in nature and can induce serious conditions by secreting type IV SS effectors (T4SEs) into the host cells. Recent studies mainly focus on annotating new T4SE...

DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks.

Briefings in bioinformatics
Protein fold recognition is critical for studying the structures and functions of proteins. The existing protein fold recognition approaches failed to efficiently calculate the pairwise sequence similarity scores of the proteins in the same fold shar...

Geographic Distribution of US Cohorts Used to Train Deep Learning Algorithms.

JAMA
This study describes the US geographic distribution of patient cohorts used to train deep learning algorithms in published radiology, ophthalmology, dermatology, pathology, gastroenterology, and cardiology machine learning articles published in 2015-...