AIMC Topic: Humans

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Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...

Initial classification of low back and leg pain based on objective functional testing: a pilot study of machine learning applied to diagnostics.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
OBJECTIVE: The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment and thus provided an adjunctive dimension in patient assessment. The clinical interpretability and confounders of the 5R-STS remain poor...

The averaged inter-brain coherence between the audience and a violinist predicts the popularity of violin performance.

NeuroImage
Why is some music well-received whereas other music is not? Previous research has indicated the close temporal dependencies of neural activity among performers and among audiences. However, it is unknown whether similar neural contingencies exist bet...

A comparison of fMRI and behavioral models for predicting inter-temporal choices.

NeuroImage
In an inter-temporal choice (IteCh) task, subjects are offered a smaller amount of money immediately or a larger amount at a later time point. Here, we are using trial-by-trial fMRI data from 363 recording sessions and machine learning in an attempt ...

Development of AOP relevant to microplastics based on toxicity mechanisms of chemical additives using ToxCastâ„¢ and deep learning models combined approach.

Environment international
Various additives are used in plastic products to improve the properties and the durability of the plastics. Their possible elution from the plastics when plastics are fragmented into micro- and nano-size in the environment is suspected to one of the...

Feature Extraction of Surface Electromyography Based on Improved Small-World Leaky Echo State Network.

Neural computation
Surface electromyography (sEMG) is an electrophysiological reflection of skeletal muscle contractile activity that can directly reflect neuromuscular activity. It has been a matter of research to investigate feature extraction methods of sEMG signals...

Preparing Medical Imaging Data for Machine Learning.

Radiology
Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The potential applications are vast and include the entirety of the medical imaging life cycle from image creation to diagnosis to outcome prediction. The chief...

A novel artificial intelligence protocol for finding potential inhibitors of acute myeloid leukemia.

Journal of materials chemistry. B
There is currently no effective treatment for acute myeloid leukemia, and surgery is also ineffective as an important treatment for most tumors. Rapidly developing artificial intelligence technology can be applied to different aspects of drug develop...

Two dimensional multifractal detrended fluctuation analysis of low coherence images for diagnosis of cervical pre-cancer.

Biomedical physics & engineering express
We report detection of cervical pre-cancer through their low coherence images by applying two dimensional multifractal detrended fluctuation analysis. Low coherent backscattered images of pre-cancerous cervical tissue sections were captured using a c...

Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.

Biomedical physics & engineering express
BACKGROUND: Magnetic resonance cine imaging is the accepted standard for cardiac functional assessment. Left ventricular (LV) segmentation plays a key role in volumetric functional quantification of the heart. Conventional manual analysis is time-con...