AIMC Topic: Machine Learning

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[Evaluation of the possibility of using neural networks for automatic diagnostics of obstructive urination].

Urologiia (Moscow, Russia : 1999)
INTRODUCTION: Obstructive type of urination requires accurate and timely diagnosis to prevent complications and improve the quality of life of patients. Traditional diagnostic methods such as uroflowmetry, although they remain the standard, have thei...

Recent Advances in Food Drying Modeling: Empirical to Multiscale Physics-Informed Neural Networks.

Comprehensive reviews in food science and food safety
Food insecurity is a major global challenge. Food preservation, particularly through drying, presents a promising solution to enhance food security and minimize waste. Fruits and vegetables contain 80%-90% water, and much of this is removed during dr...

Exploration of immune-related diagnostic biomarkers in unexplained infertility by bioinformatics analysis and machine learning.

Taiwanese journal of obstetrics & gynecology
OBJECTIVE: We aimed to discover the biomarkers associated with UI and their correlation with immune cell infiltration.

Decoupled GNNs based on multi-view contrastive learning for scRNA-seq data clustering.

Briefings in bioinformatics
Clustering is pivotal in deciphering cellular heterogeneity in single-cell RNA sequencing (scRNA-seq) data. However, it suffers from several challenges in handling the high dimensionality and complexity of scRNA-seq data. Especially when employing gr...

Identification of a Biomarker Panel in Extracellular Vesicles Derived From Non-Small Cell Lung Cancer (NSCLC) Through Proteomic Analysis and Machine Learning.

Journal of extracellular vesicles
Antigen fingerprint profiling of tumour-derived extracellular vesicles (TDEVs) in the body fluids is a promising strategy for identifying tumour biomarkers. In this study, proteomic and immunological assays reveal significantly higher CD155 levels in...

How Effective Are Machine Learning and Doubly Robust Estimators in Incorporating High-Dimensional Proxies to Reduce Residual Confounding?

Pharmacoepidemiology and drug safety
BACKGROUND: Residual confounding presents a persistent challenge in observational studies, particularly in high-dimensional settings. High-dimensional proxy adjustment methods, such as the high-dimensional propensity score (hdPS), are widely used to ...

Prediction of total phosphorus removal in hybrid constructed wetlands: a machine learning approach for rice mill wastewater treatment.

Water environment research : a research publication of the Water Environment Federation
Efficient prediction of pollutant concentrations in constructed wetlands is critical for optimizing treatment performance, yet existing methodologies often fail to account for the influence of meteorological conditions and flow rate variations in rea...

Machine-learning based classification of middle-ear fixation and separation using sweep frequency impedance information reflecting middle-ear dynamics.

The Journal of the Acoustical Society of America
The sweep frequency impedance (SFI) meter is an apparatus that delivers a frequency-sweeping sound into the ear canal and evaluates dynamic characteristics of the middle ear based on changes in sound pressure in the ear canal. We have renewed the SFI...

Machine Learning-Based Identification of Children With Intermittent Exotropia Using Multiple Resting-State Functional Magnetic Resonance Imaging Features.

Brain and behavior
OBJECTIVE: To investigate the performance of machine learning (ML) methods based on resting-state functional magnetic resonance imaging (rs-fMRI) parameters in distinguishing children with intermittent exotropia (IXT) from healthy controls (HCs).

Advancing Nutritional Status Classification With Hybrid Artificial Intelligence: A Novel Methodological Approach.

Brain and behavior
PURPOSE: Malnutrition remains a critical public health issue in low-income countries, significantly hindering economic development and contributing to over 50% of infant deaths. Under nutrition weakens immune systems, increasing susceptibility to com...