AIMC Topic: Machine Learning

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Evaluating visitor perception and spatial preferences of various museums based on machine learning from 2016 to 2024.

PloS one
Museum architecture is essential for preserving cultural heritage. Understanding the spatio-temporal evolution of visitor preferences, image perceptions, and driving factors is vital for promoting cultural development. However, traditional methods su...

Urine-based Raman markers for prostate cancer diagnosis: A machine learning approach using fingerprint and lipid spectral region.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study investigates the potential of Raman spectroscopy in distinguishing between healthy individuals and prostate cancer patients using urine samples. The Boruta algorithm was applied to Raman spectral data in two distinct wavenumber regions: 80...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

Renal failure
OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study aimed to identify immune-related diagnostic biomarkers for DKD and explore their association with imm...

Matrix-specific PFAS source allocation machine learning-based models: Identifying differential indicators in soil and water systems.

Environmental research
PER: and polyfluoroalkyl substances (PFAS) pose a significant environmental and human health risk due to their persistence, bioaccumulation, mobility, and toxicity. Current PFAS source-allocation methods often demand data on many compounds while over...

The potential of machine learning to personalized medicine in Neurogenetics: Current trends and future directions.

Computers in biology and medicine
Neurogenetic disorders (NeD) are a group of neurological conditions resulting from inherited genetic defects. By affecting the normal functioning of the nervous system, these diseases lead to serious problems in movement, cognition, and other body fu...

Integrating machine learning with in silico studies and Quantum Chemistry: Exploring novel compounds through multiscale screening targeting the CDK2 enzyme.

Computers in biology and medicine
Cyclin-dependent kinase 2 (CDK2) modulates the progression of the cell cycle, and its dysregulation results in unchecked cellular proliferation, establishing it as a pivotal target in oncological therapies. We implemented a comprehensive screening pi...

StackPIP: An Effective Computational Framework for Accurate and Balanced Identification of Proinflammatory Peptides.

Journal of chemical information and modeling
Proinflammatory peptides (PIPs) play a crucial role in immune response modulation by orchestrating cytokine release and leukocyte recruitment. Accurate identification of PIPs is essential for understanding inflammation-related diseases and developing...

MAMSI: Integration of Multiassay Liquid Chromatography-Mass Spectrometry Metabolomics Data Using Multiview Machine Learning.

Analytical chemistry
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...

Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis.

Orphanet journal of rare diseases
OBJECTIVE: Emerging evidence suggests a potential relationship between lipid metabolism and idiopathic pulmonary fibrosis (IPF). This study aimed to identify lipid-related genes implicated in IPF pathogenesis.

Application progress of machine learning in patient-ventilator asynchrony during mechanical ventilation: a systematic review.

Critical care (London, England)
INTRODUCTION: Patient-ventilator asynchrony (PVA) is a common and harmful complication during mechanical ventilation, often requiring labor-intensive manual assessment. Machine learning (ML) offers a promising approach for automated and accurate PVA ...