AIMC Topic: Algorithms

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Multi-view clustering based on feature selection and semi-non-negative anchor graph factorization.

Neural networks : the official journal of the International Neural Network Society
Multi-view clustering has garnered significant attention due to its capacity to utilize information from multiple perspectives. The concept of anchor graph-based techniques was introduced to manage large-scale data better. However, current methods re...

Leveraging Transformers-based models and linked data for deep phenotyping in radiology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Despite significant investments in the normalization and the standardization of Electronic Health Records (EHRs), free text is still the rule rather than the exception in clinical notes. The use of free text has implications...

Application of machine learning algorithms in an epidemiologic study of mortality.

Annals of epidemiology
PURPOSE: Epidemiologic studies are important in assessing risk factors of mortality. Machine learning (ML) is efficient in analyzing multidimensional data to unravel dependencies between risk factors and health outcomes.

Multi-institutional development and testing of attention-enhanced deep learning segmentation of thyroid nodules on ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: Thyroid nodules are common, and ultrasound-based risk stratification using ACR's TIRADS classification is a key step in predicting nodule pathology. Determining thyroid nodule contours is necessary for the calculation of TIRADS scores and ca...

DHCT-GAN: Improving EEG Signal Quality with a Dual-Branch Hybrid CNN-Transformer Network.

Sensors (Basel, Switzerland)
Electroencephalogram (EEG) signals are important bioelectrical signals widely used in brain activity studies, cognitive mechanism research, and the diagnosis and treatment of neurological disorders. However, EEG signals are often influenced by variou...

Predicting Gestational Diabetes Mellitus in the first trimester using machine learning algorithms: a cross-sectional study at a hospital fertility health center in Iran.

BMC medical informatics and decision making
BACKGROUND: Gestational Diabetes Mellitus (GDM) is a common complication during pregnancy. Late diagnosis can have significant implications for both the mother and the fetus. This research aims to create an early prediction model for GDM in the first...

Novel transfer learning based bone fracture detection using radiographic images.

BMC medical imaging
A bone fracture is a medical condition characterized by a partial or complete break in the continuity of the bone. Fractures are primarily caused by injuries and accidents, affecting millions of people worldwide. The healing process for a fracture ca...

Spatiotemporal analysis of land surface temperature and land cover changes in Prešov city using downscaling approach and machine learning algorithms.

Environmental monitoring and assessment
In recent decades, global climate change and rapid urbanization have aggravated the urban heat island (UHI) effect, affecting the well-being of urban citizens. Although this significant phenomenon is more pronounced in larger metropolitan areas due t...

SVM directed machine learning classifier for human action recognition network.

Scientific reports
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neura...

Explainable Machine Learning to Predict Treatment Response in Advanced Non-Small Cell Lung Cancer.

JCO clinical cancer informatics
PURPOSE: Immune checkpoint inhibitors (ICIs) have demonstrated promise in the treatment of various cancers. Single-drug ICI therapy (immuno-oncology [IO] monotherapy) that targets PD-L1 is the standard of care in patients with advanced non-small cell...