AIMC Topic: Deep Learning

Clear Filters Showing 3821 to 3830 of 28423 articles

Optimized assessment of physical rehabilitation exercises using spatiotemporal, sequential graph-convolutional networks.

Computers in biology and medicine
Rehabilitation is the process of helping people regain or improve lost or impaired function due to injury, illness, or disease. To assist in tracking the progress of patients undergoing rehabilitation, this paper proposes a lightweight graph-based de...

Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction.

NeuroImage
Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer's Disease (AD). However, changes in MRI technologies and acquisition protocols often yield limited data...

Deep learning and generative artificial intelligence in aging research and healthy longevity medicine.

Aging
With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep aging ...

Predicting Paediatric Brain Disorders from MRI Images Using Advanced Deep Learning Techniques.

Neuroinformatics
The problem at hand is the significant global health challenge posed by children's diseases, where timely and accurate diagnosis is crucial for effective treatment and management. Conventional diagnosis techniques are typical, use tedious processes a...

Mitochondrial segmentation and function prediction in live-cell images with deep learning.

Nature communications
Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image seg...

Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov-Arnold Networks.

Bioinspiration & biomimetics
The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fl...

Novel deep reinforcement learning based collision avoidance approach for path planning of robots in unknown environment.

PloS one
Reinforcement learning is a remarkable aspect of the artificial intelligence field with many applications. Reinforcement learning facilitates learning new tasks based on action and reward principles. Motion planning addresses the navigation problem f...

Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

PloS one
Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the afore...

Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent.

PloS one
Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set of assumptions that are not supported by data in high volatility markets such as the technological...

Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study.

Academic radiology
RATIONALE AND OBJECTIVES: Photon Counting CT (PCCT) offers advanced imaging capabilities with potential for substantial radiation dose reduction; however, achieving this without compromising image quality remains a challenge due to increased noise at...