AIMC Topic: Algorithms

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A simple yet effective approach for predicting disease spread using mathematically-inspired diffusion-informed neural networks.

Scientific reports Apr 29, 2025
The COVID-19 outbreak has highlighted the importance of mathematical epidemic models like the Susceptible-Infected-Recovered (SIR) model, for understanding disease spread dynamics. However, enhancing their predictive accuracy complicates parameter es...
Models, Theoretical Spain Algorithms SARS-CoV-2 Deep Learning Humans Neural Networks, Computer COVID-19
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Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Journal of medical systems Apr 29, 2025
Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF therapy and improving clinical outcomes. While machine learning (ML) has shown promise in ophthalmi...
Male Middle Aged Angiogenesis Inhibitors Retrospective Studies Female Aged Retinal Vein Occlusion Visual Acuity Macular Edema Vascular Endothelial Growth Factor A Humans Machine Learning Algorithms Prognosis
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A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.

PLoS medicine Apr 29, 2025
BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surgeries typically rely solely on preoperative clinical characteristics.
Predictive Value of Tests Vital Signs Risk Assessment Postoperative Complications Deep Learning Humans Aged Female Male Risk Factors Middle Aged Algorithms Acute Kidney Injury
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A practical approach for colorectal cancer diagnosis based on machine learning.

PloS one Apr 29, 2025
In this paper, we present the results of applying machine learning models to build a Colorectal Cancer Diagnosis system. The methodology encompasses six key steps: collecting raw data from Electronic Medical Records (EMRs), revising feature attribute...
Humans Machine Learning Algorithms Electronic Health Records Colorectal Neoplasms Diagnosis, Computer-Assisted
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NAH-GNN: A graph-based framework for multi-behavior and high-hop interaction recommendation.

PloS one Apr 29, 2025
With the growing demand for personalized marketing, recommender systems have become essential tools to help users quickly discover products or content that match their interests. However, traditional recommendation methods face significant limitation...
Humans Neural Networks, Computer Algorithms Marketing
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Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 29, 2025
Exploring the pathogenic mechanisms of brain disorders within population is an important research in the field of neuroscience. Existing methods either combine clinical information to assist analysis or use data augmentation for sample expansion, ign...
Female Male Adolescent Attention Deficit Disorder with Hyperactivity Child Machine Learning Humans Neurodevelopmental Disorders Electroencephalography Neural Networks, Computer Autoencoder Algorithms Autism Spectrum Disorder
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SMANet: A Model Combining SincNet, Multi-Branch Spatial-Temporal CNN, and Attention Mechanism for Motor Imagery BCI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 29, 2025
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an ...
Signal Processing, Computer-Assisted Attention Brain-Computer Interfaces Signal-To-Noise Ratio Movement Humans Imagination Male Deep Learning Neural Networks, Computer Electroencephalography Algorithms Adult
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Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study.

Computer methods and programs in biomedicine Apr 28, 2025
OBJECTIVE: Artificial intelligence (AI) models are effective for analyzing high-quality slit-lamp images but often face challenges in real-world clinical settings due to image variability. This study aims to develop and evaluate a hybrid AI-based ima...
Humans Artificial Intelligence Telemedicine Quality Control Cornea Algorithms Deep Learning Reproducibility of Results Image Processing, Computer-Assisted Cross-Sectional Studies
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Structural uncertainty estimation for medical image segmentation.

Medical image analysis Apr 28, 2025
Precise segmentation and uncertainty estimation are crucial for error identification and correction in medical diagnostic assistance. Existing methods mainly rely on pixel-wise uncertainty estimations. They (1) neglect the global context, leading to ...
Uncertainty Humans Neural Networks, Computer Ultrasonography Algorithms Image Processing, Computer-Assisted Reproducibility of Results Image Interpretation, Computer-Assisted
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Challenges, optimization strategies, and future horizons of advanced deep learning approaches for brain lesion segmentation.

Methods (San Diego, Calif.) Apr 28, 2025
Brain lesion segmentation is challenging in medical image analysis, aiming to delineate lesion regions precisely. Deep learning (DL) techniques have recently demonstrated promising results across various computer vision tasks, including semantic segm...
Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Algorithms Stroke Brain Neuroimaging Brain Neoplasms
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