AIMC Topic: Humans

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Machine learning-enhanced electrical impedance myography to diagnose and track spinal muscular atrophy progression.

Physiological measurement
To evaluate electrical impedance myography (EIM) in conjunction with machine learning (ML) to detect infantile spinal muscular atrophy (SMA) and disease progression.. Twenty-six infants with SMA and twenty-seven healthy infants had been enrolled and ...

Hyperspectral imaging with deep learning for quantification of tissue hemoglobin, melanin, and scattering.

Journal of biomedical optics
SIGNIFICANCE: Hyperspectral cameras capture spectral information at each pixel in an image. Acquired spectra can be analyzed to estimate quantities of absorbing and scattering components, but the use of traditional fitting algorithms over megapixel i...

Cracking the neural code for word recognition in convolutional neural networks.

PLoS computational biology
Learning to read places a strong challenge on the visual system. Years of expertise lead to a remarkable capacity to separate similar letters and encode their relative positions, thus distinguishing words such as FORM and FROM, invariantly over a lar...

Combining network pharmacology, machine learning, molecular docking and molecular dynamic to explore the mechanism of Chufeng Qingpi decoction in treating schistosomiasis.

Frontiers in cellular and infection microbiology
BACKGROUND: Although the Chufeng Qingpi Decoction (CQD) has demonstrated clinical effectiveness in the treatment of schistosomiasis, the precise active components and the underlying mechanisms of its therapeutic action remain elusive. To achieve a pr...

A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis.

PloS one
BACKGROUND: Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen g...

Diagnostic accuracy of dental caries detection using ensemble techniques in deep learning with intraoral camera images.

PloS one
Camera image-based deep learning (DL) techniques have achieved promising results in dental caries screening. To apply the intraoral camera image-based DL technique for dental caries detection and assess its diagnostic performance, we employed the ens...

Exploring a method for extracting concerns of multiple breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling.

PloS one
Narratives posted on the internet by patients contain a vast amount of information about various concerns. This study aimed to extract multiple concerns from interviews with breast cancer patients using the natural language processing (NLP) model bid...

Using machine learning to predict judgments on Western visual art along content-representational and formal-perceptual attributes.

PloS one
Art research has long aimed to unravel the complex associations between specific attributes, such as color, complexity, and emotional expressiveness, and art judgments, including beauty, creativity, and liking. However, the fundamental distinction be...