AIMC Topic: Neural Networks, Computer

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Classification and gene selection of triple-negative breast cancer subtype embedding gene connectivity matrix in deep neural network.

Briefings in bioinformatics
Triple-negative breast cancer (TNBC) has been a challenging breast cancer subtype for oncological therapy. Normally, it can be classified into different molecular subtypes. Accurate and stable classification of the six subtypes is essential for perso...

Deep learning based real-time tourist spots detection and recognition mechanism.

Science progress
More and more information on tourist spots is being represented as pictures rather than text. Consequently, tourists who are interested in a specific attraction shown in pictures may have no idea how to perform a text search to get more information a...

[Automatic Segmentation of Digital Pathology Slides Based on Unsupervised Learning].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To segment images through an unsupervised method as an alternative to manual labeling.

Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.

The Journal of the Acoustical Society of America
This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voices. Twenty-five acoustic parameters were extracted from voice samples of 203 COVID-19 patients and 17...

Measuring the importance of individual units in producing the collective behavior of a complex network.

Chaos (Woodbury, N.Y.)
A quantitative evaluation of the contribution of individual units in producing the collective behavior of a complex network can allow us to understand the potential damage to the structure integrity due to the failure of local nodes. Given a time ser...

Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network.

BMJ open gastroenterology
OBJECTIVE: Capsule endoscopy (CE) is pivotal for evaluation of small bowel disease. Obscure gastrointestinal bleeding most often originates from the small bowel. CE frequently identifies a wide range of lesions with different bleeding potentials in t...

A comparative biology approach to DNN modeling of vision: A focus on differences, not similarities.

Journal of vision
Deep neural networks (DNNs) have revolutionized computer science and are now widely used for neuroscientific research. A hot debate has ensued about the usefulness of DNNs as neuroscientific models of the human visual system; the debate centers on to...

Evaluation of the prediction of CoVID-19 recovered and unrecovered cases using symptoms and patient's meta data based on support vector machine, neural network, CHAID and QUEST Models.

European review for medical and pharmacological sciences
OBJECTIVE: This paper aims to develop four prediction models for recovered and unrecovered cases using descriptive data of patients and symptoms of CoVID-19 patients. The developed prediction models aim to extract the important variables in predictin...

Training for object recognition with increasing spatial frequency: A comparison of deep learning with human vision.

Journal of vision
The ontogenetic development of human vision and the real-time neural processing of visual input exhibit a striking similarity-a sensitivity toward spatial frequencies that progresses in a coarse-to-fine manner. During early human development, sensiti...

Which deep learning model can best explain object representations of within-category exemplars?

Journal of vision
Deep neural network (DNN) models realize human-equivalent performance in tasks such as object recognition. Recent developments in the field have enabled testing the hierarchical similarity of object representation between the human brain and DNNs. Ho...