AIMC Topic: Datasets as Topic

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Automatic knee meniscus tear detection and orientation classification with Mask-RCNN.

Diagnostic and interventional imaging
PURPOSE: This work presents our contribution to a data challenge organized by the French Radiology Society during the Journées Francophones de Radiologie in October 2018. This challenge consisted in classifying MR images of the knee with respect to t...

Evolution of Deep Convolutional Neural Networks Using Cartesian Genetic Programming.

Evolutionary computation
The convolutional neural network (CNN), one of the deep learning models, has demonstrated outstanding performance in a variety of computer vision tasks. However, as the network architectures become deeper and more complex, designing CNN architectures...

LUADpp: an effective prediction model on prognosis of lung adenocarcinomas based on somatic mutational features.

BMC cancer
BACKGROUND: Lung adenocarcinoma is the most common type of lung cancers. Whole-genome sequencing studies disclosed the genomic landscape of lung adenocarcinomas. however, it remains unclear if the genetic alternations could guide prognosis prediction...

Large-scale network analysis reveals the sequence space architecture of antibody repertoires.

Nature communications
The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we...

Five simultaneous artificial intelligence data challenges on ultrasound, CT, and MRI.

Diagnostic and interventional imaging
PURPOSE: The goal of this data challenge was to create a structured dynamic with the following objectives: (1) teach radiologists the new rules of General Data Protection Regulation (GDPR), while building a large multicentric prospective database of ...

Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database.

PloS one
BACKGROUND: Intelligent decision support systems (IDSS) have been applied to tasks of disease management. Deep neural networks (DNNs) are artificial intelligent techniques to achieve high modeling power. The application of DNNs to large-scale data fo...

Predicting protein-peptide interaction sites using distant protein complexes as structural templates.

Scientific reports
Protein-peptide interactions play an important role in major cellular processes, and are associated with several human diseases. To understand and potentially regulate these cellular function and diseases it is important to know the molecular details...

Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies.

Scientific reports
Data are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but recently there has been a move to combine multipl...

Predicting one-year outcome in first episode psychosis using machine learning.

PloS one
BACKGROUND: Early illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier intervention corresponds to significantly better symptomatic and functional outcomes. Our study object...

Significant improvement of miRNA target prediction accuracy in large datasets using meta-strategy based on comprehensive voting and artificial neural networks.

BMC genomics
BACKGROUND: Identifying mRNA targets of miRNAs is critical for studying gene expression regulation at the whole-genome level. Multiple computational tools have been developed to predict miRNA:mRNA interactions. Nonetheless, many of these tools are de...