AIMC Topic: Machine Learning

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Predicting cortical-thalamic functional connectivity using functional near-infrared spectroscopy and graph convolutional networks.

Scientific reports
Functional near-infrared spectroscopy (fNIRS) measures cortical hemodynamic changes, yet it cannot collect this information from subcortical structures, such as the thalamus, which is involved in several key functional networks. To address this drawb...

Machine learning analysis of the effects of COVID-19 on migration patterns.

Scientific reports
This study investigates the impact of the COVID-19 pandemic on European tourist mobility patterns from 2019 to 2021 by conceptualizing countries as monomers emitting radiation to model and analyze their patterns through the lens of socio-economics an...

Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea.

Scientific reports
This study aimed to develop and validate a machine learning (ML)-based model for predicting liposuction volumes in patients with obesity. This study used longitudinal cohort data from 2018 to 2023 from five nationwide centers affiliated with 365MC Li...

Advances in artificial intelligence-based technologies for increasing the quality of medical products.

Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences
Artificial intelligence (AI) is a technology that combines machine learning (ML) and deep learning. It has numerous usages in the domains of medicine and other sciences. Artificial intelligence can forecast the behavior of a drug's target protein and...

Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction.

Biological psychiatry
BACKGROUND: Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. However, opioid addiction treatments have limited efficacy, meaning that additional...

Development and Validation of a Machine Learning Radiomics Model based on Multiparametric MRI for Predicting Progesterone Receptor Expression in Meningioma: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a machine learning-based prediction model for preoperatively predicting progesterone receptor (PR) expression in meningioma patients using multiparametric magnetic resonance imaging (...

An adaptive session-incremental broad learning system for continuous motor imagery EEG classification.

Medical & biological engineering & computing
Motor imagery electroencephalography (MI-EEG) is usually used as a driving signal in neuro-rehabilitation systems, and its feature space varies with the recovery progress. It is required to endow the recognition model with continuous learning and sel...

Hybrid contrastive multi-scenario learning for multi-task sequential-dependence recommendation.

Neural networks : the official journal of the International Neural Network Society
Multi-scenario and multi-task learning are crucial in industrial recommendation systems to deliver high-quality recommendations across diverse scenarios with minimal computational overhead. However, conventional models often fail to effectively lever...

Projected response of algal blooms in global lakes to future climatic and land use changes: Machine learning approaches.

Water research
The eutrophication of lakes and the subsequent algal blooms have become significant environmental issues of global concern in recent years. With ongoing global warming and intensifying human activities, water quality trends in lakes worldwide varied ...

Riemannian manifold-based disentangled representation learning for multi-site functional connectivity analysis.

Neural networks : the official journal of the International Neural Network Society
Functional connectivity (FC), derived from resting-state functional magnetic resonance imaging (rs-fMRI), has been widely used to characterize brain abnormalities in disorders. FC is usually defined as a correlation matrix that is a symmetric positiv...