AIMC Topic: Machine Learning

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A novel hybrid model for species distribution prediction using probabilistic random forest, principal component analysis and genetic algorithm.

PloS one
Probabilistic Random Forest is an extension of the traditional Random Forest machine learning algorithm that is one of the frequently used machine learning algorithms employed for species distribution modeling. However, with the use of complex datase...

HLX and SLC25A20: Immunologic regulators bridging ankylosing spondylitis and uveitis via multi-omics integration and machine learning.

PloS one
BACKGROUND: Ankylosing spondylitis (AS), a chronic inflammatory disorder affecting axial joints, is frequently complicated by uveitis. However, the molecular mechanisms linking AS to secondary uveitis remain poorly understood.

A hybrid framework of statistical, machine learning, and explainable AI methods for school dropout prediction.

PloS one
Student dropout is a significant challenge in Bangladesh, with serious impacts on both educational and socio-economic outcomes. This study investigates the factors influencing school dropout among students aged 6-24 years, employing data from the 201...

An updated vocal repertoire of wild adult bonobos (Pan paniscus).

PloS one
Research over the last 20 years has shed important light on the vocal behaviour of our closest living relatives, bonobos and chimpanzees, but mostly relies on qualitative vocal repertoires, for which quantitative validations are absent. Such data are...

Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

PloS one
BACKGROUND: In order to seriously impact the global burden of heart failure (HF) and coronary artery disease (CAD), identifying at-risk individuals as early as possible is vital. Risk calculator tools in wide clinical use today are informed by tradit...

Machine Learning-Aided Screening and Design Rule Discovery for LWIR-Transparent Optical Materials.

Journal of chemical information and modeling
The development of low-cost, high-performance materials with enhanced transparency in the long-wavelength infrared (LWIR) region (800-1250 cm/8-12.5 μm) is essential for advancing thermal imaging and sensing technologies. Traditional LWIR optics rely...

Statin-dependent and -independent pathways are associated with major adverse cardiovascular events in people with HIV.

The Journal of clinical investigation
BACKGROUNDStatin therapy lowers the risk of major adverse cardiovascular events (MACE) among people with HIV (PWH). Residual risk pathways contributing to excess MACE beyond LDL-cholesterol (LDL-C) are not well understood. Our objective was to evalua...

Integrative multi-omics identifies S100A8/IGFBP5/CTSK/S100P as dual diagnostic biomarkers and therapeutic targets in Crohn's disease: from computational discovery to preclinical validation.

International immunopharmacology
Crohn's disease (CD) is a chronic inflammatory bowel condition that significantly impairs patients' quality of life. With no cure currently available, the need to discover novel biomarkers and develop effective therapeutic strategies is paramount. Th...

A multiomics recovery factor predicts long COVID in the IMPACC study.

The Journal of clinical investigation
BACKGROUNDFollowing SARS-CoV-2 infection, approximately 10%-35% of patients with COVID-19 experience long COVID (LC), in which debilitating symptoms persist for at least 3 months. Elucidating the biologic underpinnings of LC could identify therapeuti...

Exploring the Frontiers of Computational NMR: Methods, Applications, and Challenges.

Chemical reviews
Computational methods have revolutionized NMR spectroscopy, driving significant advancements in structural biology and related fields. This review focuses on recent developments in quantum chemical and machine learning approaches for computational NM...