AIMC Topic: Machine Learning

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Improving attachment style clustering with ROCKET and CatBoost: Insights from EEG analysis.

PloS one
Understanding attachment styles is essential in psychology and neuroscience, yet predicting them using objective neural data remains challenging. This study explores the use of machine learning (ML) models and EEG analysis to improve attachment style...

Investigating factors influencing fatalities and injuries in animal-vehicle crashes using a random parameters logit model and ensemble machine learning approaches.

PloS one
Animal-vehicle crashes (AVC) pose risks in rural areas, often leading to casualties and injuries. Despite their infrequent occurrence, AVC can have significant consequences, especially when larger animals are involved. This study investigates factors...

Prediction of Activity and Selectivity Profiles of Sigma Receptor Ligands Using Machine Learning Approaches.

Journal of chemical information and modeling
Sigma (σ) receptors (SRs) have emerged as important therapeutic targets due to their roles in various biological pathways. They are classified into two subtypes: S1R, primarily distributed in the central nervous system and related to neuroprotection ...

The efficacy of machine learning algorithms in evaluating factors associated with shunt-dependent hydrocephalus after subarachnoid hemorrhage: a systematic review and meta-analysis.

Neurosurgical review
The identification of factors associated with chronic shunt-dependent hydrocephalus (CSDH) following spontaneous subarachnoid hemorrhage (SAH) remains challenging, despite numerous studies. Early recognition of patients at higher risk for requiring s...

ACO1 OGDH axis drives mitochondrial immune crosstalk in preeclampsia through systems biology enabling dual target therapy.

Scientific reports
Preeclampsia (PE), a devastating pregnancy complication affecting 5% of gravidas worldwide, exhibits poorly characterized connections between mitochondrial dysfunction and immune dysregulation. This study aims to identify integrated mitochondrial-imm...

Fibro predict a machine learning risk score for advanced liver fibrosis in the general population using Israeli electronic health records.

Scientific reports
Liver diseases, notably cirrhosis, pose a substantial global health challenge, resulting in millions of annual deaths. Existing diagnostic methods primarily target high-risk groups, leaving a significant portion of patients undiagnosed. This study ai...

Machine learning-based transcriptomic analysis identifies candidate genes in sepsis-induced coagulopathy and explores the immunomodulatory potential of baicalein.

Human genomics
BACKGROUND: Sepsis is a major contributor to high morbidity and mortality, often leading to coagulation disorders (CD) in affected individuals. Baicalein, a natural compound with well-established anti-inflammatory properties, shows promise as a poten...

Divergent biological pathways distinguish community-acquired pneumonia from COVID-19 despite similar plasma cytokine profiles.

Respiratory research
BACKGROUND: Pulmonary infections, ranging from mild respiratory issues to severe multiorgan failure, pose a major global health threat. The immune response in community-acquired pneumonia (CAP) and COVID-19 influences disease severity and outcomes, b...

Factors associated with admission to elderly medical-welfare facilities in South Korea: a cross-sectional machine-learning study.

BMJ open
OBJECTIVES: To identify the key factors associated with admission to elderly medical-welfare facilities in South Korea and to evaluate their relative importance using machine learning techniques, providing an evidence base for policy in a rapidly age...

Explainable machine learning for comprehensive characterization of poly (6-(Ethoxybenzothiazole acrylamide)) resin for removal of Th(IV), As(V), and Hg(II) ions from aqueous solution.

Environmental geochemistry and health
Adsorption is a promising technique with significant potential for water purification. In this context, the present study examines the adsorption efficiency of poly(6-(ethoxybenzothiazole acrylamide) (PEBTA) in removing high-valent metal ions from aq...