AIMC Topic: Humans

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White matter hyperintensities segmentation using the ensemble U-Net with multi-scale highlighting foregrounds.

NeuroImage
White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the human brain MRI and have been associated with aging processes, cognitive decline, and dementia. In the current study, we proposed a U-Net with multi-scale...

Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design.

Drug metabolism and pharmacokinetics
The objective of this study was to obtain the indicators of physicochemical parameters and structurally active sites to design new chemical entities with desirable pharmacokinetic profiles by investigating the process by which machine learning predic...

Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation.

Small methods
Nanoparticles occur in various environments as a consequence of man-made processes, which raises concerns about their impact on the environment and human health. To allow for proper risk assessment, a precise and statistically relevant analysis of pa...

Texture analysis based on U-Net neural network for intracranial hemorrhage identification predicts early enlargement.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Early hemorrhage enlargement in hypertensive cerebral hemorrhage indicates a poor prognosis. This study aims to predict the early enlargement of cerebral hemorrhage through the intelligent texture analysis of cerebral hemorr...

Learning-based defect recognition for quasi-periodic HRSTEM images.

Micron (Oxford, England : 1993)
Controlling crystalline material defects is crucial, as they affect properties of the material that may be detrimental or beneficial for the final performance of a device. Defect analysis on the sub-nanometer scale is enabled by high-resolution scann...

The Translational Machine: A novel machine-learning approach to illuminate complex genetic architectures.

Genetic epidemiology
The Translational Machine (TM) is a machine learning (ML)-based analytic pipeline that translates genotypic/variant call data into biologically contextualized features that richly characterize complex variant architectures and permit greater interpre...

The Function of Color and Structure Based on EEG Features in Landscape Recognition.

International journal of environmental research and public health
Both color and structure make important contributions to human visual perception, as well as the evaluation of landscape quality and landscape aesthetics. The EEG equipment liveamp32 was used to record the EEG signals of humans when viewing landscape...

Development and Validation of a Deep Learning Model to Quantify Interstitial Fibrosis and Tubular Atrophy From Kidney Ultrasonography Images.

JAMA network open
IMPORTANCE: Interstitial fibrosis and tubular atrophy (IFTA) is a strong indicator of decline in kidney function and is measured using histopathological assessment of kidney biopsy core. At present, a noninvasive test to assess IFTA is not available.