AIMC Topic: Algorithms

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A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field.

BioMed research international
One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the facto...

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning i...

Systematic evaluation of machine learning algorithms for neuroanatomically-based age prediction in youth.

Human brain mapping
Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the ML approach in estimating brain-age i...

Traceable machine learning real-time quality control based on patient data.

Clinical chemistry and laboratory medicine
OBJECTIVES: Patient-based real-time quality control (PBRTQC) has gained attention as an alternative/integrative tool for internal quality control (iQC). However, it is still doubted for its performance and its application in real clinical settings. W...

Sparse signal reconstruction via collaborative neurodynamic optimization.

Neural networks : the official journal of the International Neural Network Society
In this paper, we formulate a mixed-integer problem for sparse signal reconstruction and reformulate it as a global optimization problem with a surrogate objective function subject to underdetermined linear equations. We propose a sparse signal recon...

Convolutional Neural Networks in Spinal Magnetic Resonance Imaging: A Systematic Review.

World neurosurgery
OBJECTIVE: Convolutional neural networks (CNNs) are being increasingly used in the medical field, especially for image recognition in high-resolution, large-volume data sets. The study represents the current state of research on the application of CN...

Assessing the robustness of clinical trials by estimating Jadad's score using artificial intelligence approaches.

Computers in biology and medicine
BACKGROUND: Clinical trials are essential in medical science and are currently the most robust strategy for evaluating the effectiveness of a treatment. However, some of these studies are less reliable than others due to flaws in their design. Assess...

Artificial intelligence in retinal imaging for cardiovascular disease prediction: current trends and future directions.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Retinal microvasculature assessment has shown promise to enhance cardiovascular disease (CVD) risk stratification. Integrating artificial intelligence into retinal microvasculature analysis may increase the screening capacity of CV...

Adaptive Dense Ensemble Model for Text Classification.

IEEE transactions on cybernetics
Text classification has been widely explored in natural language processing. In this article, we propose a novel adaptive dense ensemble model (AdaDEM) for text classification, which includes local ensemble stage (LES) and global dense ensemble stage...

Kullback-Leibler Divergence-Based Fuzzy C-Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation.

IEEE transactions on cybernetics
In this article, we elaborate on a Kullback-Leibler (KL) divergence-based Fuzzy C -Means (FCM) algorithm by incorporating a tight wavelet frame transform and morphological reconstruction (MR). To make membership degrees of each image pixel closer to ...