AIMC Topic: Deep Learning

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Deep learning analyses of splicing variants identify the link of PCP4 with amyotrophic lateral sclerosis.

Brain : a journal of neurology
Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease, with most sporadic cases lacking clear genetic causes. Abnormal pre-mRNA splicing is a fundamental mechanism in neurodegenerative diseases. For example, TAR DNA-binding protein 43 ...

Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning.

Brain : a journal of neurology
The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As demand for thrombectomy rises and geographical disparities in stroke...

A deep learning model for structure-based bioactivity optimization and its application in the bioactivity optimization of a SARS-CoV-2 main protease inhibitor.

European journal of medicinal chemistry
Bioactivity optimization is a crucial and technical task in the early stages of drug discovery, traditionally carried out through iterative substituent optimization, a process that is often both time-consuming and expensive. To address this challenge...

Rapid diagnosis of lung cancer by multi-modal spectral data combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Lung cancer is a malignant tumor that poses a serious threat to human health. Existing lung cancer diagnostic techniques face the challenges of high cost and slow diagnosis. Early and rapid diagnosis and treatment are essential to improve the outcome...

AI-guided cryo-EM analysis untangles uromodulin lattices that safeguard kidneys.

Structure (London, England : 1993)
In this issue of Structure, Chang et al. combined deep-learning cryoelectron microscopy (cryo-EM) particle picking and heterogeneous refinement to obtain structures of human uromodulin filament lattices that were isolated from urine samples. This wor...

Contrast-enhanced image synthesis using latent diffusion model for precise online tumor delineation in MRI-guided adaptive radiotherapy for brain metastases.

Physics in medicine and biology
Magnetic resonance imaging-guided adaptive radiotherapy (MRIgART) is a promising technique for long-course radiotherapy of large-volume brain metastasis (BM), due to the capacity to track tumor changes throughout treatment course. Contrast-enhanced T...

Self-supervised learning for low-dose CT image denoising method based on guided image filtering.

Physics in medicine and biology
low-dose computed tomography (LDCT) images suffer from severe noise due to reduced radiation exposure. Most existing deep learning-based denoising methods require supervised learning with paired training data that is difficult to obtain. To address t...

Deep learning on high-density EEG during a cognitive task distinguishes patients with Parkinson's disease from healthy controls.

Journal of neural engineering
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms, including cognitive impairment. Its diagnosis, which used to be based on clinical assessment, increasingly relies on biomarkers. While electroence...

Annotating neurophysiologic data at scale with optimized human input.

Journal of neural engineering
Neuroscience experiments and devices are generating unprecedented volumes of data, but analyzing and validating them presents practical challenges, particularly in annotation. While expert annotation remains the gold standard, it is time consuming to...

Dual-Mode Temperature-Pressure MXene Sensor for Enhanced Firefighter Safety and Deep Learning-Enhanced Smart Gloves.

ACS applied materials & interfaces
Dual-mode sensors capable of detecting multiple physical stimuli simultaneously offer significant advantages for advanced applications in human-machine interaction, robotics, and healthcare. However, the flammability of conventional materials limits ...