AIMC Topic: Deep Learning

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Both Infarcted and Noninfarcted Brain Regions Contribute to Deep Learning-Based MRI Prediction of Acute Stroke Outcome.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Predicting long-term clinical outcomes based on early acute ischemic stroke (AIS) information would be useful for many reasons, including patient counseling and clinical trial execution. This study investigates how different r...

Artificial Intelligence-Driven Detection of Large Vessel Occlusions on NCCT: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Imaging triage of stroke patients is primarily based on perfusion imaging. Simplified triage based on non-contrast CT are limited (NCCT). To evaluate the predictive capability of a deep learning algorithm, "Triage Stroke" (Bra...

Brain tumour segmentation in fused MRI-PET images with permutate U-Net framework.

PloS one
Brain tumor segmentation from MRI's and PET has always been a challenging and time-consuming phase for radiologists, due to low sensitivity boundary region pixels in this image modality. Deep learning-based image segmentation is the hot research topi...

Capsule-based federated reinforcement learning adaptive sliding mode for anomaly detection and control of floating wind turbines.

PloS one
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under significant osc...

Advances in deep reinforcement learning enable better predictions of human behavior in time-continuous tasks.

PloS one
Humans have to respond to everyday tasks with goal-directed actions in complex and time-continuous environments. However, modeling human behavior in such environments has been challenging. Deep Q-networks (DQNs), an application of deep learning used ...

Decoding brand sentiments: Leveraging customer reviews for insightful brand perception analysis using natural language processing and Tableau.

PloS one
Traditional survey-based feedback has given way to real-time online reviews, yet transforming this unstructured text into actionable knowledge remains difficult. Focusing on the highly competitive smartphone market, where customer sentiment shapes br...

ProSECFPs: A Novel Fingerprint-Based Protein Representation Method for Missense Mutation Pathogenicity Prediction.

Journal of chemical information and modeling
Developing effective computational representations of protein sequences is crucial for advancing diverse areas of computational biology and bioinformatics. Ideal representations must be computationally efficient, scalable, informative, flexible acros...

Usefulness of Data Simulation for Training Deep Learning Denoising Algorithms in Infrared Spectral Histology.

Analytical chemistry
This study investigates the use of simulated data to train deep learning models for denoising infrared spectral images of paraffin-embedded tissue sections in clinical applications. Noise in Fourier-transform infrared spectroscopy poses significant c...

Sensitive detection of structural dynamics using a statistical framework for comparative crystallography.

Science advances
Chemical and conformational changes are crucial to protein function and its pharmacological control. X-ray crystallography can reveal these changes in atomic detail, but standard analysis methods, which refine separate datasets, often overlook differ...

Aerobatic maneuvers in insect-scale flapping-wing aerial robots via deep-learned robust tube model predictive control.

Science advances
Aerial insects exhibit agile maneuvers such as sharp braking, saccades, and body flips under disturbances; in contrast, insect-scale aerial robots are limited to tracking smooth trajectories with small acceleration. To achieve similar flight capabili...