AIMC Topic: Machine Learning

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Clinically interpretable electrovectorcardiographic machine learning criteria for the detection of echocardiographic left ventricular hypertrophy.

PloS one
Echocardiographic left ventricular hypertrophy (Echo-LVH) is frequently underdetected by traditional electrocardiogram (ECG) criteria due to limited sensitivity. We investigated whether integrating ECG with vectorcardiography (VCG) using a clinically...

Analysis of spatial heterogeneity in Xi'an's urban heat island effect using multi-source data fusion.

PloS one
In the context of global climate change, this study aims to investigate the spatial heterogeneity and driving mechanisms of the urban heat island (UHI) effect within Xi'an's second ring road area. We constructed a novel multi-source data fusion frame...

Neurophysiological mechanisms and predictive modeling of SSRI treatment response in depression disorder based on multidimensional EEG features.

Journal of affective disorders
BACKGROUND: Depression exhibits significant heterogeneity in antidepressant treatment response. This study aimed to develop an Electroencephalography (EEG)-based machine learning model integrating multidimensional features to predict selective seroto...

Discovery of Comprehensive Sets of Chemical Constituents as Markers of PFAS Sources through a Nontarget Screening and Machine Learning Approach.

Environmental science & technology
The objective of this study was to identify chemical constituents as markers of six per- and polyfluoroalkyl substance (PFAS) sources including aqueous film-forming foam-impacted groundwater, landfill leachate, biosolids leachate, municipal wastewate...

Serum Fingerprinting-Based Integrative Dual-Omics Machine Learning for Endometriosis-Associated Ovarian Cancer.

Analytical chemistry
Dual-omics, by integrating molecular information from two distinct dimensions, can offer more comprehensive perspective for complex disease. Herein, we developed an efficient functionalized mesoporous nanoparticle-coupled laser desorption/ionization ...

ANABAG: Annotated Antibody-Antigen Data Set with Unique Features for Antibody Engineering Applications.

Journal of chemical information and modeling
The analysis and prediction of antibody-antigen (Ab-Ag) interactions often overlook critical structural features such as glycosylation and important physicochemical conditions like pH and salt concentration. Additionally, the field lacks standardized...

Chemical Space of Molecular Nanomotors: Optimizing Photochemical Properties for One- and Two-Photon Applications.

Journal of chemical information and modeling
Light-driven molecular nanomotors hold promise for applications in materials science and biomedicine. Significant efforts have focused on improving their efficiency, often targeting single candidate molecules. Here, we present a systematic, data-driv...

T cell receptor specificity landscape revealed through de novo peptide design.

Proceedings of the National Academy of Sciences of the United States of America
T cells play a key role in adaptive immunity by mounting specific responses against diverse pathogens. Effective bindings between T cell receptors (TCRs) and pathogen derived peptides presented on major histocompatibility complexes (MHCs) mediate imm...

Association between atherogenic index of plasma and sepsis in critically ill patients with ischemic stroke: a retrospective cohort study using propensity score and machine learning approaches.

Lipids in health and disease
BACKGROUND: Sepsis is a severe and frequent complication among ischemic stroke patients during hospitalization. The atherogenic index of plasma (AIP), as metabolism-related markers, are closely linked to inflammation. However, their relationship with...

Integrated machine learning identifies biomarkers for bilirubin-induced Alzheimer's disease-like lesions in neonates and adults.

Scientific reports
Neurological impairments resulting from bilirubin encephalopathy represent a hallmark of bilirubin's neurotoxic effects. Earlier research suggests that bilirubin may contribute to Alzheimer's disease (AD) pathology by inducing neuronal necrosis and a...