AIMC Topic: Humans

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Reliability of uncertainty quantification methods for deep learning auto-segmentation in head and neck organs at risk.

Physics in medicine and biology
Deep learning auto-segmentation has greatly advanced contouring in radiotherapy. However, quality assurance remains necessary due to performance fluctuation among individual patients. This manual process reintroduces variability and partially reduces...

Res-MoCoDiff: residual-guided diffusion models for motion artifact correction in brain MRI.

Physics in medicine and biology
Motion artifacts (ARTs) in brain magnetic resonance imaging (MRI), mainly from rigid head motion, degrade image quality and hinder downstream applications. Conventional methods to mitigate these ARTs, including repeated acquisitions or motion trackin...

E-Sort: empowering end-to-end neural network for multi-channel spike sorting with transfer learning and fast post-processing.

Journal of neural engineering
Spike sorting, which involves detecting and attributing spikes to their putative neurons from extracellular recordings, is a common process in electrophysiology and brain-computer interface systems. Recent advances in large-scale neural recording tec...

Spatial domain identification method based on multi-view graph convolutional network and contrastive learning.

PLoS computational biology
Spatial transcriptomics is a rapidly developing field of single-cell genomics that quantitatively measures gene expression while providing spatial information within tissues. A key challenge in spatial transcriptomics is identifying spatially structu...

Enhanced heart disease diagnosis and management: A multi-phase framework leveraging deep learning and personalized nutrition.

PloS one
In health care, an accurate diagnosis with the help of a data-driven forecasting framework takes the risk factors associated with heart disease. However, building such an effective model using deep learning (DL) methods requires high-quality data, i....

Nonlinear control of a fully actuated robotic hand using high-order sliding mode and feedback linearization controllers.

PloS one
The increasing adoption of prosthetic devices in medical applications introduces complex and variable load conditions, particularly due to the diverse nature of user disabilities. To address the resulting control challenges, this paper proposes a nov...

Clinically interpretable electrovectorcardiographic machine learning criteria for the detection of echocardiographic left ventricular hypertrophy.

PloS one
Echocardiographic left ventricular hypertrophy (Echo-LVH) is frequently underdetected by traditional electrocardiogram (ECG) criteria due to limited sensitivity. We investigated whether integrating ECG with vectorcardiography (VCG) using a clinically...

AI-driven 3D CT imaging prediction model for improving preoperative detection of visceral pleural invasion in early-stage lung cancer.

PloS one
Visceral pleural invasion (VPI) is a critical prognostic factor in early-stage non-small-cell lung cancer (NSCLC), significantly affecting patient outcomes. Conventional computed tomography (CT) often fails to diagnose VPI accurately. This retrospect...

Analysis of spatial heterogeneity in Xi'an's urban heat island effect using multi-source data fusion.

PloS one
In the context of global climate change, this study aims to investigate the spatial heterogeneity and driving mechanisms of the urban heat island (UHI) effect within Xi'an's second ring road area. We constructed a novel multi-source data fusion frame...

4-Hydroxy-2,5-dihydrothiazole derivatives as a new class of small-molecule antibiotics for MRSA: AI-integrated design, chemical synthesis and biological evaluation.

European journal of medicinal chemistry
Staphylococcus aureus (S. aureus) is one of the most concerned Gram-positive bacteria due to its resistance to the commonly used antibiotics, methicillin. To address the threat of methicillin-resistant S. aureus (MRSA), new classes of antibiotics are...