AIMC Topic: Deep Learning

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A systematic review: Brain age gap as a promising early diagnostic biomarker for Alzheimer's disease.

Journal of the neurological sciences
Alzheimer's disease (AD) is a progressive neurodegenerative disorder for which there is currently no cure, and its incidence is on the rise. Early detection is essential for timely intervention and slowing the progression of the disease. While the br...

Gradient-driven pixel connectivity convolutional neural networks classification based on U-Net lung nodule segmentation.

Medical engineering & physics
Lung cancer is a significant global health issue, heavily burdening healthcare systems. Early detection is crucial for improving patient outcomes. This study proposes a diagnostic aid system for the early detection and classification of lung nodules ...

Disruption of Hsp70.14-BAG2 Protein-Protein interactions using deep Learning-Driven peptide design and molecular simulations.

Computers in biology and medicine
Protein-protein interactions (PPIS) are critical in proteostasis, stress response, and disease progression. Targeting the interaction between Hsp70.14 and BAG2, a co-chaperone implicated in oncogenic survival, offers a promising therapeutic approach....

Artificial intelligence in bone metastasis analysis: Current advancements, opportunities and challenges.

Computers in biology and medicine
BACKGROUND: Artificial Intelligence is transforming medical imaging, particularly in the analysis of bone metastases (BM), a serious complication of advanced cancers. Machine learning and deep learning techniques offer new opportunities to improve de...

DFT_ANPD: A dual-feature two-sided attention network for anticancer natural products detection.

Computers in biology and medicine
The exploration of anticancer drugs has aimed at more effective, adaptable, and less harmful treatments, with natural products pivotal in cancer research. In addition to experimental techniques for identifying anticancer drug candidates, computationa...

Radiomics and deep learning characterisation of liver malignancies in CT images - A systematic review.

Computers in biology and medicine
BACKGROUND: Computed tomography (CT) has been widely used as an effective tool for liver imaging due to its high spatial resolution, and ability to differentiate tissue densities, which contributing to comprehensive image analysis. Recent advancement...

Pollen morphology, deep learning, phylogenetics, and the evolution of environmental adaptations in Podocarpus.

The New phytologist
Podocarpus pollen morphology is shaped by both phylogenetic history and the environment. We analyzed the relationship between pollen traits quantified using deep learning and environmental factors within a comparative phylogenetic framework. We inves...

Explainable RNA-Small Molecule Binding Affinity Prediction Based on Multiview Enhancement Learning.

Journal of chemical information and modeling
RNA has the potential to serve as a drug target, requiring RNA-small molecule binding affinity to screen potential drugs generally. However, accurately predicting RNA-small molecule binding affinity remains a highly challenging task. This study propo...

DeepGFT: identifying spatial domains in spatial transcriptomics of complex and 3D tissue using deep learning and graph Fourier transform.

Genome biology
The rapid advancements in spatially resolved transcriptomics (SRT) enable the characterization of gene expressions while preserving spatial information. However, high dropout rates and noise hinder accurate spatial domain identification for understan...