AIMC Topic: Machine Learning

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Machine Learning for Group-Targeted Elution Order Prediction: Substituted Flavones as a Case Study.

Journal of chemical information and modeling
Prediction of the elution order of close structural analogs and isomers is a critical step in plant metabolites dereplication. The application of machine learning (ML) is an efficient approach to automate peak annotation by implementing structure-ret...

C-reactive protein-triglyceride glucose index in predicting three-vessel coronary artery disease risk: a retrospective study using machine learning approaches.

Annals of medicine
BACKGROUND: Three-vessel coronary artery disease (TVD) is a severe subtype of coronary heart disease, strongly associated with inflammation and metabolic dysfunction. The C-reactive protein-triglyceride glucose index (CTI), an integrated measure of i...

Machine learning-based preliminary screening tool for clinical pregnancy prediction: towards management of IVF/ICSI stages.

Annals of medicine
BACKGROUND: Accurate prediction of pregnancy outcomes in assisted reproductive technology (ART) remains a clinical challenge due to the complexity and heterogeneity of IVF/ICSI cycles. Existing models often focus on isolated treatment stages and rely...

Machine learning combined with body composition predicts surgical difficulty in mid-low rectal cancer surgery.

Annals of medicine
BACKGROUND: This study sought to identify critical body composition characteristics associated with surgical difficulty in Laparoscopic Total Mesorectal Excision (LaTME) and to develop and validate an interpretable machine learning model using body c...

Machine learning identification of influencing factors of global Nation-Level hypertension prevalence.

BMC public health
Hypertension remains a critical global public health challenge, with its complex etiology poorly captured by traditional linear models, especially regarding macro-level structural and gender-specific drivers. To address this, we employed an interpret...

A comparison of computational methods for expression forecasting.

Genome biology
Diverse machine learning methods promise to forecast gene expression changes in response to novel genetic perturbations. However, these methods' accuracy is not well characterized. We created a benchmarking platform that combines a panel of 11 large-...

Machine learning-enhanced prediction of fetal growth restriction using fetal cardiac remodeling parameters.

BMC medicine
BACKGROUND: Fetal growth restriction (FGR) contributes to over 30% of late-pregnancy stillbirth, yet its diagnosis is challenging because current methods rely on indirect surrogate markers (estimated fetal weight and umbilical artery) that often fail...

Integrating machine learning and molecular dynamics simulation to decipher the molecular network of dioxin-associated liposarcoma.

Scientific reports
Dioxin-like pollutants, especially 2,3,7,8-Tetrachlorodibenzo-p-dioxin, are recognized human carcinogens. Retrospective studies suggest a link between dioxins and soft tissue sarcomas, including liposarcoma, but mechanisms remain unclear. This study ...

Revisiting successful aging through a machine learning approach to quantifying the influence of chronic diseases.

Scientific reports
Chronic diseases are highly prevalent among older adults and may be associated with their ability to achieve successful aging, which encompasses five key components: absence of major chronic diseases, freedom from disability, high cognitive function,...

TL-PneuNet: a transfer learning-based pneumonia classification framework.

Scientific reports
Pneumonia is a severe respiratory ailment that may be caused by viruses, fungus, and bacteria. Pneumonia causes the accumulation of water, purulent material, or other fluids in the air sacs (alveoli) of the lungs. A delay in the identification of pne...