AIMC Topic: Machine Learning

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Development of the Screen for Child Anxiety Related Emotional Disorders (SCARED) optimal short scale for Chinese children and adolescents: based on FasterRisk machine learning modeling.

BMC public health
BACKGROUND: Although the Screen for Child Anxiety Related Emotional Disorders (SCARED) is a widely used tool for assessing anxiety, its 41-item format makes it a time-intensive method for identifying children and adolescents at high risk of anxiety. ...

Edge computing with federated learning for early detection of citric acid overdose and adjustment of regional citrate anticoagulation.

BMC medical informatics and decision making
Regional citrate anticoagulation (RCA) is critical for extracorporeal anticoagulation in continuous renal replacement therapy done at the bedside. To make patients' data more secure and to help with computer-based monitoring of dosages, we suggest a ...

Predicting the risk of threatened abortion using machine learning methods: a comparative study.

BMC pregnancy and childbirth
BACKGROUND AND OBJECTIVE: Threatened abortion, a common pregnancy complication that often leading to abortion, is hard to predict due to its non-specific symptoms and difficulty in differentiating from other early pregnancy bleeding causes. Current d...

Trait mediation explains decadal distributional shifts for a wide range of insect taxa.

Nature communications
Shifts in insect distributions have been reported globally, largely attributed to climate and landscape changes. Communities are being reshaped, with species response traits mediating the effects of changing environments. Using a machine-learning app...

Machine learning-based prediction of drinking water quality index in Western Tehran using KAN, MLP, and traditional models.

Environmental monitoring and assessment
In this study, the water quality index (WQI) was calculated using multivariate statistics, incorporating physical, chemical, and microbiological analysis of water samples taken from water supply networks in the western district of Tehran from 2021 to...

Comparative analysis of multiple machine learning models: identifying impact factors in biochar heavy metal adsorption mechanisms.

Environmental geochemistry and health
The contribution analysis of influencing factors governing biochar-mediated heavy metal adsorption in aqueous systems holds significant implications for cost-effective water remediation. Current studies predominantly rely on single-model approaches t...

Machine learning integration of bulk and single-cell RNA-seq data reveals glycolytic heterogeneity in colorectal cancer.

Medical oncology (Northwood, London, England)
As one of the most prevalent malignancies worldwide, colorectal cancer (CRC) exhibits a strong metabolic dependency on glycolysis, which fuels tumor expansion and shapes an immunosuppressive microenvironment. Despite its clinical significance, the re...

Exploring potential associations and biomarkers linked polycystic ovarian syndrome with atherosclerosis via comprehensive bioinformatics analysis, machine learning, and animal experiments.

Functional & integrative genomics
Polycystic ovary syndrome (PCOS), a common endocrine condition affecting multiple systems, is tied to atherosclerosis (AS) progression among reproductive-aged women. The present study aimed to explore the underlying associations and uncover potential...

Integrated Microbiome Data Analysis Reveals Potential Pneumonia Microbial Biomarkers in ICU Patients: A Machine Learning Approach.

Current microbiology
The human microbiome is pivotal in maintaining health and managing diseases. By examining the core microbiome in intensive care units (ICU) patients with pneumonia, we can gain valuable insights into the microbial communities associated with disease ...

Using Environmental Mixture Exposure-Triggered Biological Knowledge-Driven Machine Learning to Predict Early Pregnancy Loss.

Environmental science & technology
The assessment of how environmental mixture exposures affect reproductive health faces difficulties. While knowledge graph networks offer valuable advantages in biological interpretation and prediction, their application in epidemiological studies, p...