AIMC Topic: Algorithms

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Stacking Ensemble Deep Learning for Real-Time Intrusion Detection in IoMT Environments.

Sensors (Basel, Switzerland)
The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling advanced patient care through interconnected medical devices and systems. However, its critical role and sensitive data make it a prime target for cyber threats, requirin...

Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Cohort studies contain rich clinical data across large and diverse patient populations and are a common source of observational data for clinical research. Because large scale cohort studies are both time and resource intensive, one alter...

Joint embedding-classifier learning for interpretable collaborative filtering.

BMC bioinformatics
BACKGROUND: Interpretability is a topical question in recommender systems, especially in healthcare applications. An interpretable classifier quantifies the importance of each input feature for the predicted item-user association in a non-ambiguous f...

Medical image segmentation based on frequency domain decomposition SVD linear attention.

Scientific reports
Convolutional Neural Networks (CNNs) have achieved remarkable segmentation accuracy in medical image segmentation tasks. However, the Vision Transformer (ViT) model, with its capability of extracting global information, offers a significant advantage...

Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.

Nature communications
Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackl...

DAU-Net: a novel U-Net with dual attention for retinal vessel segmentation.

Biomedical physics & engineering express
In fundus images, precisely segmenting retinal blood vessels is important for diagnosing eye-related conditions, such as diabetic retinopathy and hypertensive retinopathy or other eye-related disorders. In this work, we propose an enhanced U-shaped n...

CDCG-UNet: Chaotic Optimization Assisted Brain Tumor Segmentation Based on Dilated Channel Gate Attention U-Net Model.

Neuroinformatics
Brain tumours are one of the most deadly and noticeable types of cancer, affecting both children and adults. One of the major drawbacks in brain tumour identification is the late diagnosis and high cost of brain tumour-detecting devices. Most existin...

Harnessing machine learning algorithms for the prediction and optimization of various properties of polylactic acid in biomedical use: a comprehensive review.

Biomedical materials (Bristol, England)
Machine learning (ML) has emerged as a transformative tool in various industries, driving advancements in key tasks like classification, regression, and clustering. In the field of chemical engineering, particularly in the creation of biomedical devi...

Development of a machine learning tool to predict deep inspiration breath hold requirement for locoregional right-sided breast radiation therapy patients.

Biomedical physics & engineering express
. This study presents machine learning (ML) models that predict if deep inspiration breath hold (DIBH) is needed based on lung dose in right-sided breast cancer patients during the initial computed tomography (CT) appointment.. Anatomic distances wer...

Prediction Trough Concentrations of Valproic Acid Among Chinese Adult Patients with Epilepsy Using Machine Learning Techniques.

Pharmaceutical research
OBJECTIVE: This study aimed to establish an optimal model based on machine learning (ML) to predict Valproic acid (VPA) trough concentrations in Chinese adult epilepsy patients.