AIMC Topic: Deep Learning

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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.

BMC geriatrics
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts health care worldwide, particularly among the elderly population. The accurate classification of AD stages is essential for slowing disease progression an...

Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics.

Communications biology
In eukaryotic cells, DNA replication is organised both spatially and temporally, as evidenced by the stage-specific spatial distribution of replication foci in the nucleus. Despite the genetic association of aberrant DNA replication with numerous hum...

SmartAPM framework for adaptive power management in wearable devices using deep reinforcement learning.

Scientific reports
Wearable devices face a significant challenge in balancing battery life with performance, often leading to frequent recharging and reduced user satisfaction. In this paper, we introduce the SmartAPM (Smart Adaptive Power Management) framework, a nove...

A labeled medical records corpus for the timely detection of rare diseases using machine learning approaches.

Scientific reports
Rare diseases (RDs) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world's population. Most of them affect children, are chronic and progressive, and have no specific treatment....

Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features.

Scientific reports
Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especially in regions with limited access to medical expertise. However, existing methods often overlook edge pixel information during tumor segmentation, l...

Deep-learning tool for early identification of non-traumatic intracranial hemorrhage etiology and application in clinical diagnostics based on computed tomography (CT) scans.

PeerJ
BACKGROUND: To develop an artificial intelligence system that can accurately identify acute non-traumatic intracranial hemorrhage (ICH) etiology (aneurysms, hypertensive hemorrhage, arteriovenous malformation (AVM), Moyamoya disease (MMD), cavernous ...

Author name disambiguation based on heterogeneous graph neural network.

PloS one
With the dramatic increase in the number of published papers and the continuous progress of deep learning technology, the research on name disambiguation is at a historic peak, the number of paper authors is increasing every year, and the situation o...

Intelligent larval zebrafish phenotype recognition via attention mechanism for high-throughput screening.

Computers in biology and medicine
BACKGROUND: Larval zebrafish phenotypes serve as critical research indicators in fields such as ecotoxicology and safety assessment since phenotypic defects are closely related to alterations of underlying pathway. However, identifying these defects ...

Multiscale Dissection of Spatial Heterogeneity by Integrating Multi-Slice Spatial and Single-Cell Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The spatial structure of cells is highly organized at multiscale levels from global spatial domains to local cell type heterogeneity. Existing methods for analyzing spatially resolved transcriptomics (SRT) are separately designed for either domain al...